Meritxell Bach Cuadra

2022-01-01. 13th International Workshop on Computational Diffusion MRI (CDMRI), Singapore, SINGAPORE, Sep 22, 2022. p. 3-13. DOI : 10.1007/978-3-031-21206-2_1.

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BMAT: An open-source BIDS managing and analysis tool

C. Vanden Bulcke; M. Wynen; J. Detobel; F. La Rosa; M. Absinta et al.

Neuroimage-Clinical. 2022-01-01. DOI : 10.1016/j.nicl.2022.103252.

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Combining Model Driven and Data Driven Approaches for Inverse Problems in Parameter Estimation and Image Reconstruction: From Modelling to Validation

T. Yu / J.-P. Thiran; M. Bach Cuadra (Dir.)

Lausanne, EPFL, 2022. DOI : 10.5075/epfl-thesis-9693.

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Deep learning-based analysis of multiple sclerosis lesions with high and ultra-high field MRI

F. La Rosa / J.-P. Thiran; M. Bach Cuadra (Dir.)

Lausanne, EPFL, 2022. DOI : 10.5075/epfl-thesis-9571.

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Automated detection of cortical lesions with single and multi-contrast 7T MRI

F. La Rosa; E. S. Beck; J. Maranzano; J. -P. Thiran; C. Granziera et al.

2021-10-01. p. 458-459.

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Cortical lesion detection using FLAWS in multiple sclerosis

J. Muller; R. Rahmanzadeh; C. Tsagkas; M. Barakovic; P. -J. Lu et al.

2021-10-01. p. 433-434.

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An assessment of intra-scanner reproducibility of myelin-sensitive MRI measures

R. Rahmanzadeh; M. Weigel; P. -J. Lu; L. Melie-Garcia; T. D. Nguyen et al.

2021-10-01. p. 430-431.

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CLaiMS-Net: cortical lesions assessment in multiple sclerosis patients via a convolutional neural network and a single 3T MRI acquisition

F. La Rosa; P. -J. Lu; R. Rahmanzadeh; A. Cagol; M. Barakovic et al.

2021-10-01. p. 457-458.

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Chronic White Matter Inflammation and Serum Neurofilament Levels in Multiple Sclerosis

P. Maggi; J. Kuhle; S. Schadelin; F. van der Meer; M. Weigel et al.

Neurology. 2021-08-10. DOI : 10.1212/WNL.0000000000012326.

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Fetal Brain Biometric Measurements on 3D Super-Resolution Reconstructed T2-Weighted MRI: An Intra- and Inter-observer Agreement Study

M. Khawam; P. de Dumast; P. Deman; H. Kebiri; T. Yu et al.

Frontiers In Pediatrics. 2021-08-10. DOI : 10.3389/fped.2021.639746.

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An automatic multi-tissue human fetal brain segmentation benchmark using the Fetal Tissue Annotation Dataset

K. Payette; P. de Dumast; H. Kebiri; I. Ezhov; J. C. Paetzold et al.

Scientific Data. 2021-07-06. DOI : 10.1038/s41597-021-00946-3.

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Myelin and axon pathology in multiple sclerosis assessed by myelin water and multi-shell diffusion imaging

R. Rahmanzadeh; P.-J. Lu; M. Barakovic; M. Weigel; P. Maggi et al.

Brain. 2021-06-01. DOI : 10.1093/brain/awab088.

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Automated assessment of paramagnetic rim lesions in multiple sclerosis patients with 3T and 7T MP2RAGE

F. La Rosa; G. Barquero; O. Al-Louzi; B. M. Maréchal Mortamet; T. Kober et al.

2021-05-15. The 2021 ISMRM & SMRT Annual Meeting & Eshibition, [Online], 15-20 may, 2021.

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GAMER-MRI in Multiple Sclerosis Identifies the Diffusion-Based Microstructural Measures That Are Most Sensitive to Focal Damage: A Deep-Learning-Based Analysis and Clinico-Biological Validation

P.-J. Lu; M. Barakovic; M. Weigel; R. Rahmanzadeh; R. Galbusera et al.

Frontiers In Neuroscience. 2021-04-06. DOI : 10.3389/fnins.2021.647535.

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MPRAGE to MP2RAGE UNI translation via generative adversarial network improves the automatic tissue and lesion segmentation in multiple sclerosis patients

F. La Rosa; T. Yu; G. Barquero; J.-P. Thiran; C. Granziera et al.

Computers in Biology and Medicine. 2021-02-26. DOI : 10.1016/j.compbiomed.2021.104297.

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Simulated Half-Fourier Acquisitions Single-shot Turbo Spin Echo (HASTE) of the Fetal Brain: Application to Super-Resolution Reconstruction

H. Lajous; T. Hilbert; C. W. Roy; S. Tourbier; P. de Dumast et al.

2021-01-01. 3rd Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging (UNSURE) / 6th International Workshop on Preterm, Perinatal and Paediatric Image Analysis (PIPPI), ELECTR NETWORK, Sep 27-Oct 01, 2021. p. 157-167. DOI : 10.1007/978-3-030-87735-4_15.

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Quantitative Evaluation of Enhanced Multi-plane Clinical Fetal Diffusion MRI with a Crossing-Fiber Phantom

H. Kebiri; H. Lajous; Y. Aleman-Gomez; G. Girard; E. C. Rodriguez et al.

2021-01-01. 12th International Workshop on Computational Diffusion MRI (CDMRI), ELECTR NETWORK, Oct 01, 2021. p. 12-22. DOI : 10.1007/978-3-030-87615-9_2.

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GAMER MRI: Gated-attention mechanism ranking of multi-contrast MRI in brain pathology

P.-J. Lu; Y. Yoo; R. Rahmanzadeh; R. Galbusera; M. Weigel et al.

Neuroimage-Clinical. 2021-01-01. DOI : 10.1016/j.nicl.2020.102522.

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Model-informed machine learning for multi-component T2 relaxometry

T. Yu; E. J. Canales Rodriguez; M. Pizzolato; G. F. Piredda; T. Hilbert et al.

Medical Image Analysis. 2020-12-17. DOI : 10.1016/j.media.2020.101940.

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A step forward toward the fully automated assessment of the central vein sign

M. J. Fartaria; O. Al-Louzi; T. Huelnhagen; L. Daboul; P. Maggi et al.

2020-12-01. 8th Joint ACTRIMS-ECTRIMS Meeting (MSVirtual), ELECTR NETWORK, Sep 11-13, 2020. p. 7-7.

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Rimnet: a deep 3D multimodal MRI architecture for paramagnetic rim lesions assessment in multiple sclerosis

G. Barquero; F. La Rosa; H. Kebiri; P. -J. Lu; R. Rahmanzadeh et al.

2020-12-01. 8th Joint ACTRIMS-ECTRIMS Meeting (MSVirtual), ELECTR NETWORK, Sep 11-13, 2020. p. 36-36.

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Quantitative susceptibility mapping classifies white matter lesions with different myelin and axonal content and quantifies diffuse pathology in MS

R. Rahmanzadeh; P. -J. Lu; M. Barakovic; M. Weigel; T. D. Nguyen et al.

2020-12-01. 8th Joint ACTRIMS-ECTRIMS Meeting (MSVirtual), ELECTR NETWORK, Sep 11-13, 2020. p. 29-30.

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Studying intralesional axonal damage in ms white matter lesions with diffusion mri biophysical models

M. Barakovic; R. Rahmanzadeh; P. -J. Lu; P. Maggi; M. Absinta et al.

2020-12-01. 8th Joint ACTRIMS-ECTRIMS Meeting (MSVirtual), ELECTR NETWORK, Sep 11-13, 2020. p. 426-427.

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Advanced magnetic resonance imaging for myelin and axonal density in ms: correlation with clinical disability and serum neurofilament levels

R. Rahmanzadeh; P. -J. Lu; M. Barakovic; M. Weigel; S. Schaedelin et al.

2020-12-01. 8th Joint ACTRIMS-ECTRIMS Meeting (MSVirtual), ELECTR NETWORK, Sep 11-13, 2020. p. 372-372.

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Translating mprage to mp2rage improves the automatic tissue and lesion segmentation in multiple sclerosis patients

F. La Rosa; T. Yu; G. Barquero; J. -P. Thiran; C. Granziera et al.

2020-12-01. 8th Joint ACTRIMS-ECTRIMS Meeting (MSVirtual), ELECTR NETWORK, Sep 11-13, 2020. p. 125-126.

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Evolution of Cortical and White Matter Lesion Load in Early-Stage Multiple Sclerosis: Correlation With Neuroaxonal Damage and Clinical Changes

R.-A. Todea; P.-J. Lu; M. J. Fartaria; G. Bonnier; R. Du Pasquier et al.

Frontiers In Neurology. 2020-09-04. DOI : 10.3389/fneur.2020.00973.

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RimNet: A deep 3D multimodal MRI architecture for paramagnetic rim lesion assessment in multiple sclerosis

G. Barquero; F. La Rosa; H. Kebiri; P.-J. Lu; R. Rahmanzadeh et al.

NeuroImage: Clinical. 2020-09-04. DOI : 10.1016/j.nicl.2020.102412.

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Partial-volume modeling reveals reduced gray matter in specific thalamic nuclei early in the time course of psychosis and chronic schizophrenia

Y. Aleman-Gomez; E. Najdenovska; T. Roine; M. J. Fartaria; E. J. Canales-Rodriguez et al.

Human Brain Mapping. 2020-07-10. DOI : 10.1002/hbm.25108.

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Multiple sclerosis cortical and WM lesion segmentation at 3T MRI: a deep learning method based on FLAIR and MP2RAGE

F. La Rosa; A. Abdulkadir; M. J. Fartaria; R. Rahmanzadeh; P.-J. Lu et al.

NeuroImage: Clinical. 2020-06-30. DOI : 10.1016/j.nicl.2020.102335.

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Normalization of aberrant pretherapeutic dynamic functional connectivity of extrastriate visual system in patients who underwent thalamotomy with stereotactic radiosurgery for essential tremor: a resting-state functional MRI study

C. Tuleasca; T. A. W. Bolton; J. Regis; E. Najdenovska; T. Witjas et al.

Journal Of Neurosurgery. 2020-06-01. DOI : 10.3171/2019.2.JNS183454.

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Higher Order Spherical Harmonics Reconstruction of Fetal Diffusion MRI With Intensity Correction

M. Deprez; A. Price; D. Christiaens; G. L. Estrin; L. Cordero-Grande et al.

Ieee Transactions On Medical Imaging. 2020-04-01. DOI : 10.1109/TMI.2019.2943565.

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CVSnet: A machine learning approach for automated central vein sign assessment in multiple sclerosis

P. Maggi; M. J. Fartaria; J. Jorge; F. La Rosa; M. Absinta et al.

Nmr In Biomedicine. 2020-03-03. DOI : 10.1002/nbm.4283.

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Improved susceptibility-weighted imaging for high contrast and resolution thalamic nuclei mapping at 7T

J. Jorge; F. Gretsch; E. Najdenovska; C. Tuleasca; M. Levivier et al.

Magnetic Resonance In Medicine. 2020-02-12. DOI : 10.1002/mrm.28197.

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Quantification in Musculoskeletal Imaging Using Computational Analysis and Machine Learning: Segmentation and Radiomics

M. B. Cuadra; P. Omoumi

Seminars In Musculoskeletal Radiology. 2020-02-01. DOI : 10.1055/s-0039-3400268.

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Resting-state functional MRI for functional neurosurgery: seeing the light?

C. Tuleasca; J. Regis; E. Najdenovska; T. Witjas; N. Girard et al.

Journal Of Neurosurgery. 2019-10-01. DOI : 10.3171/2019.1.JNS1995.

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Deep learning-based detection of cortical lesions in multiple sclerosis patients with FLAIR, DIR, and MP2RAGE MRI sequences

F. La Rosa; M. J. Fartaria; A. Abdulkadir; R. Rahmanzadeh; P.-J. Lu et al.

2019-09-10. 35th Congress of the European-Committee-for-Treatment-and-Research-in-Multiple-Sclerosis (ECTRIMS), Stockholm, Sweden, September 11-13, 2019. p. 131-356. DOI : 10.1177/1352458519868078.

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Deep learning analysis applied to multi-parametric advanced MRI shows higher myelin content and neurite density in juxtacortical lesions compared to periventricular lesions

P. -J. Lu; R. Rahmanzadeh; R. Galbusera; B. Odry; M. Weigel et al.

2019-09-01. 35th Congress of the European-Committee-for-Treatment-and-Research-in-Multiple-Sclerosis (ECTRIMS) / 24th Annual Conference of Rehabilitation in MS, Stockholm, SWEDEN, Sep 11-13, 2019. p. 241-242.

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A fully automated approach for differential diagnosis support in multiple sclerosis based on the central vein sign

M. J. Fartaria; P. Maggi; P. Sati; D. S. Reich; C. Granziera et al.

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Deep learning-based detection of cortical lesions in multiple sclerosis patients with FLAIR, DIR, and MP2RAGE MRI sequences

F. La Rosa; M. J. Fartaria; A. Abdulkadir; R. Rahmanzadeh; P. -J. Lu et al.

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Axonal and myelin injury in white matter and cortex of relapsing-remitting and progressive multiple sclerosis patients: a combined myelin water and multi-shell diffusion MRI study

R. Rahmanzadeh; P. -J. Lu; M. Weigel; R. Galbusera; T. D. Nguyen et al.

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Axonal damage explains part of and extends beyond the diffuse pathology evidenced by T1 mapping in normal-appearing white matter of multiple sclerosis patients

R. Rahmanzadeh; P. -J. Lu; M. Weigel; R. Galbusera; F. La Rosa et al.

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Automated Detection and Segmentation of Multiple Sclerosis Lesions Using Ultra-High-Field MP2RAGE

M. J. Fartaria; P. Sati; A. Todea; E.-W. Radue; R. Rahmanzadeh et al.

Investigative Radiology. 2019-06-01. DOI : 10.1097/RLI.0000000000000551.

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Episodic memory decline in Parkinson' s disease: relation with white matter hyperintense lesions and influence of quantification method

V. Dunet; M. J. Fartaria; J. Deverdun; E. Le Bars; F. Maury et al.

Brain Imaging And Behavior. 2019-06-01. DOI : 10.1007/s11682-018-9909-x.

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A Novel Spatial-Angular Domain Regularisation Approach for Restoration of Diffusion MRI

A. Mella; A. Daducci; G. Orlandi; J.-P. Thiran; M. Deprez et al.

2019-01-01. 21st International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI) / 8th Eurographics Workshop on Visual Computing for Biology and Medicine (VCBM) / International Workshop on Computational Diffusion MRI (CDMRI), Granada, SPAIN, Sep 16-21, 2018. p. 43-53. DOI : 10.1007/978-3-030-05831-9_4.

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Longitudinal analysis of white matter and cortical lesions in multiple sclerosis

M. J. Fartaria; T. Kober; C. Granziera; M. B. Cuadra

Neuroimage-Clinical. 2019-01-01. DOI : 10.1016/j.nicl.2019.101938.

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Letter: Deep Brain Stimulation of the Pedunculopontine Nucleus Area in Parkinson Disease: Magnetic Resonance Imaging- Based Anatomoclinical Correlations and Optimal Target

C. Tuleasca; J. Regis; E. Najdenovska; T. Witjas; N. Girard et al.

Neurosurgery. 2019-01-01. DOI : 10.1093/neuros/nyy516.

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Comparison of MRI-based automated segmentation methods and functional neurosurgery targeting with direct visualization of the Ventro-intermediate thalamic nucleus at 7T

E. Najdenovska; C. Tuleasca; J. Jorge; P. Maeder; J. P. Marques et al.

Scientific Reports. 2019. DOI : 10.1038/s41598-018-37825-8.

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Pretherapeutic resting-state fMRI profiles are associated with MR signature volumes after stereotactic radiosurgical thalamotomy for essential tremor

C. Tuleasca; J. Regis; E. Najdenovska; T. Witjas; N. Girard et al.

Journal Of Neurosurgery. 2018-12-01. DOI : 10.3171/2018.7.GKS18752.

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In-vivo probabilistic atlas of human thalamic nuclei based on diffusion-weighted magnetic resonance imaging

E. Najdenovska; Y. Aleman-Gomez; G. Battistella; M. Descoteaux; P. Hagmann et al.

Scientific Data. 2018-11-27. DOI : 10.1038/sdata.2018.270.

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Personalized Anatomic Eye Model From T1-Weighted Volume Interpolated Gradient Echo Magnetic Resonance Imaging of Patients With Uveal Melanoma

H.-G. Nguyen; R. Sznitman; P. Maeder; A. Schalenbourg; M. Peroni et al.

International Journal Of Radiation Oncology Biology Physics. 2018-11-15. DOI : 10.1016/j.ijrobp.2018.05.004.

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Accuracy versus reproducibility: comprehensive assessment of four automated methods for multiple sclerosis lesion segmentation

M. J. Fartaria; R. Corredor-Jerez; J. Richiardi; B. Marechal; C. Granziera et al.

2018-10-01. 34th Congress of the European-Committee-for-Treatment-and-Research-in-Multiple-Sclerosis (ECTRIMS), Berlin, GERMANY, Oct 10-12, 2018. p. 359-359.

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Automated assessment of new and enlarged white matter and cortical lesions in early multiple sclerosis

M. J. Fartaria; G. Bonnier; T. Kober; M. B. Cuadra; C. Granziera

2018-10-01. 34th Congress of the European-Committee-for-Treatment-and-Research-in-Multiple-Sclerosis (ECTRIMS), Berlin, GERMANY, Oct 10-12, 2018. p. 570-570.

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Differential diagnosis of multiple sclerosis with machine learning-based central vein sign recognition

J. Richiardi; P. Maggi; M. J. Fartaria; F. La Rosa; J. Jorge et al.

2018-10-01. 34th Congress of the European-Committee-for-Treatment-and-Research-in-Multiple-Sclerosis (ECTRIMS), Berlin, GERMANY, Oct 10-12, 2018. p. 530-531.

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Shallow vs deep learning architectures for white matter lesion segmentation in the early stages of multiple sclerosis

F. La Rosa; M. J. Fartaria; T. Kober; J. Richiardi; C. Granziera et al.

2018-09-10. BrainLes Workshop, MICCAI 2018, Granada, Spain, September 16, 2018. DOI : 10.1007/978-3-030-11723-8_14.

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Ocular Structures Segmentation from Multi-sequences MRI Using 3D Unet with Fully Connected CRFs

Huu-Giao Nguyen; A. Pica; P. Maeder; A. Schalenbourg; M. Peroni et al.

2018-01-01. 1st International Workshop on Computational Pathology (COMPAY) / 5th International Workshop on Ophthalmic Medical Image Analysis (OMIA), Granada, SPAIN, Sep 16-20, 2018. p. 167-175. DOI : 10.1007/978-3-030-00949-6_20.

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Visually-sensitive networks in essential tremor: evidence from structural and functional imaging

C. Tuleasca; J. Régis; E. Najdenovska; T. Witjas; N. Girard et al.

Brain. 2018. DOI : 10.1093/brain/awy094.

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Assessing the clinical outcome of Vim radiosurgery with voxel-based morphometry: visual areas are linked with tremor arrest!

C. Tuleasca; T. Witjas; E. Najdenovska; A. Verger; N. Girard et al.

Acta Neurochirurgica. 2017. DOI : 10.1007/s00701-017-3317-7.

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An Ultra-High Field Study of Cerebellar Pathology in Early Relapsing-Remitting Multiple Sclerosis Using MP2RAGE

M. J. Fartaria; K. O'Brien; A. Sorega; G. Bonnier; A. Roche et al.

Investigative Radiology. 2017. DOI : 10.1097/Rli.0000000000000338.

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Automatic Segmentation of the Eye in 3D Magnetic Resonance Imaging: A Novel Statistical Shape Model for Treatment Planning of Retinoblastoma

C. Ciller; S. I. De Zanet; M. B. Rueegsegger; A. Pica; R. Sznitman et al.

International Journal Of Radiation Oncology Biology Physics. 2015. DOI : 10.1016/j.ijrobp.2015.02.056.

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A Multi-Contrast MRI Study of Microstructural Brain Damage in Patients with Mild Cognitive Impairment

C. Granziera; A. Daducci; A. Donati; G. Bonnier; D. Romascano et al.

NeuroImage: Clinical. 2015. DOI : 10.1016/j.nicl.2015.06.003.

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Landmark Detection for Fusion of Fundus and MRI Toward a Patient-Specific Multimodal Eye Model

S. I. De Zanet; C. Ciller; T. Rudolph; P. Maeder; F. Munier et al.

Ieee Transactions On Biomedical Engineering. 2015. DOI : 10.1109/Tbme.2014.2359676.

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An evaluation of volume-based morphometry for prediction of mild cognitive impairment and Alzheimer's disease

D. Schmitter; A. Roche; B. Maréchal; D. Ribes; A. Abdulkadir et al.

NeuroImage: Clinical. 2015. DOI : 10.1016/j.nicl.2014.11.001.

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Volume-based vs. voxel-based brain morphometry in Alzheimer's disease prediction

A. Roche; D. A. Schmitter; B. M. Maréchal Mortamet; D. Ribes Lemay; A. Abdulkadir et al.

2014. 23rd International Society for Magnetic Resonance in Medicine (ISMRM) Conference, Milan, Italy, May 10-16, 2014.

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Semi-Supervised Segmentation of Ultrasound Images Based on Patch Representation and Continuous Min Cut

A. Ciurte; X. Bresson; O. Cuisenaire; N. Houhou; S. Nedevschi et al.

Plos One. 2014. DOI : 10.1371/journal.pone.0100972.

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MBIS: Multivariate Bayesian Image Segmentation tool

O. Esteban; G. Wollny; S. Gorthi; M.-J. Ledesma-Carbayo; J.-P. Thiran et al.

Computer Methods And Programs In Biomedicine. 2014. DOI : 10.1016/j.cmpb.2014.03.003.

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Evaluation and Comparison of Current Fetal Ultrasound Image Segmentation Methods for Biometric Measurements: A Grand Challenge

S. Rueda; S. Fathima; C. L. Knight; M. Yaqub; A. T. Papageorghiou et al.

Ieee Transactions On Medical Imaging. 2014. DOI : 10.1109/Tmi.2013.2276943.

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Simulation-based evaluation of susceptibility distortion correction methods in diffusion MRI for connectivity analysis

O. Esteban; A. Daducci; E. Caruyer; K. O'Brien; L. Carbayo et al.

2014. IEEE 11th International Symposium on Biomedical Imaging - From Nano to Macro (ISBI), Beijing, China, April 29 - May 2, 2014. p. 738-741. DOI : 10.1109/ISBI.2014.6867976.

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A NEW APPROACH FOR CEREBELLO-THALAMIC MOTOR NETWORK EVALUATION IN ASYMPTOMATIC PREMUTATION CARRIERS AT RISK FOR FXTAS

G. Battistella; N. Ghazaleh; E. Fornari; E. Najdenovska; M. Bach Cuadra et al.

Human Brain Mapping, Seattle, USA, June 16-20, 2013.

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Weighted Shape-Based Averaging With Neighborhood Prior Model for Multiple Atlas Fusion-Based Medical Image Segmentation

S. Gorthi; M. Bach Cuadra; P.-A. Tercier; A. S. Allal; J.-P. Thiran

IEEE Signal Processing Letters. 2013. DOI : 10.1109/LSP.2013.2279269.

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Multi Atlas Fusion Methods for Medical Image Segmentation

S. Venkata Ravi Mohana Sai Gorthi / J.-P. Thiran (Dir.)

Lausanne, EPFL, 2013. DOI : 10.5075/epfl-thesis-5747.

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Towards a connectome mapping pipeline for neonates using high-resolution MP2RAGE and DTI

A. Pauli; J. Schneider; M. Bach Cuadra; A. Griffa; E. Fischi Gomez et al.

2013. 21st Annual Meeting International Society for Magnetic Resonance in Medicine, Salt Lake City, Utah, USA, April 20-26,2013.

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Multi-atlas fusion methods for segmentation of head and neck lymph nodes for radiotherapy planning

S. Gorthi; M. Bach Cuadra; J. Villafruela Vicario; P.-A. Tercier; J.-P. Thiran et al.

2013. 2nd ESTRO Forum, Geneva, April 19-23, 2013.

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Atlas-free brain tissue segmentation using a single T1-weighted MRI acquisition

T. Kober; A. Roche; O. Esteban-Sanz; S. Gorthi; D. Ribes et al.

2012. International Society for Magnetic Resonance in Medicine (ISMRM), Melbourne, Australia, May 5-11.

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STATISTICAL MODELING OF THE EYE FOR MULTIMODAL TREATMENT PLANNING FOR EXTERNAL BEAM RADIOTHERAPY OF INTRAOCULAR TUMORS

M. RUEEGSEGGER; M. Bach Cuadra; A. Pica; C. AMSTUTZ; T. RUDOLPH et al.

International Journal of Radiation Oncology, Biology, Physics.. 2012. DOI : 10.1016/j.ijrobp.2012.05.040.

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Brain tissue segmentation on diffusion weighted magnetic resonance data

O. Esteban-Sanz; S. Gorthi; G. Wollny; A. Daducci; M. J. Ledesma-Carbayo et al.

2012. IEEE International Symposium on Biomedical Imaging (ISBI) 2012, Barcelona, Spain, 2-5 May 2012.

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Evaluation of Atlas Fusion Strategies for Segmentation of Head and Neck Lymph Nodes for Radiotherapy Planning

S. Gorthi; M. Bach Cuadra; U. Schick; P.-A. Tercier; A. S. Allal et al.

2012. IEEE International Symposium on Biomedical Imaging (ISBI), Barcelona, Spain, May 2-5, 2012. p. 1276-1279. DOI : 10.1109/ISBI.2012.6235795.

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How to Measure Cortical Folding from MR Images: a Step-by-Step Tutorial to Compute Local Gyrification Index

M. Schaer; M. Bach Cuadra; N. Schmansky; B. Fischl; J.-P. Thiran et al.

Journal of Visualized Experiments. 2012. DOI : 10.3791/3417.

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A pipeline approach with spatial information for segmenting multiple sclerosis lesions on brain magnetic resonance imaging

M. Cabezas Grebol; M. Bach Cuadra; A. Oliver; X. Lladó; J. Freixenet et al.

5th Joint triennial congress of the European and Americas committees for treatment and research in multiple sclerosis, Amsterdam, The Netherlands, October 19-22, 2011.

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Fusion of Multi-Atlas Segmentations with Spatial Distribution Modeling

S. Gorthi; M. Bach Cuadra; U. Schick; P.-A. Tercier; A. S. Allal et al.

2011. MICCAI Worskshop on Multi-Atlas Labeling and Statistical Fusion, Toronto, Canada, September, 18-22, 2011.

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On the Convergence of EM-Like Algorithms for Image Segmentation using Markov Random Fields

A. Roche; D. Ribes; M. Bach Cuadra; G. Krüger

Medical Image Analysis -Elsevier-. 2011. DOI : 10.1016/j.media.2011.05.002.

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Towards a diffusion image processing validation and accuracy prediction framework

F. Pizzorni Ferrarese; A. Daducci; M. Bach Cuadra; A. Lemkaddem; C. Granziera et al.

2011. IEEE International Conference on Image Processing, Brussel, Belgium, September 11-14, 2011. p. 2269-2272. DOI : 10.1109/ICIP.2011.6116091.

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Comparison of Energy Minimization Methods for 3-D Brain Tissue Classification

S. Gorthi; J.-P. Thiran; M. Bach Cuadra

2011. IEEE International Conference on Image Processing, Brussels, Belgium, September 11-14, 2011. p. 57-60. DOI : 10.1109/ICIP.2011.6116615.

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Review on Atlas-based Segmentation of Magnetic Resonance Brain Images

M. Cabezas Grebol; A. Oliver; X. Llado; J. Freixenet; M. Bach Cuadra

Computer Methods and Programs in Biomedicine. 2011. DOI : 10.1016/j.cmpb.2011.07.015.

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Comparison of tissue classification models for automatic brain MR segmentation

D. Ribes; B. Mortamet; M. Bach Cuadra; C. Jack; R. Meuli et al.

19th Annual Meeting and Exhibition ISMRM, Montreal, Quebec, Canada, May 7-13, 2011.

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Quantitative morphometry analysis of the fetal brain using clinical MR imaging

M. Bach Cuadra; G. V. Bonanno; L. Guibaud; S. Eliez; J.-P. Thiran et al.

19th Annual Meeting and Exhibition ISMRM, Montreal, Quebec, Canada, May 7-13.

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3D Ultrasound Tumor Segmentation and Fusion with CT for Stereotactic Radiation Therapy Planning of Retinoblastoma

A. Pica; F. I. Karahanoglu; A.-R. Ciurte; S. Gorthi; A. Balmer et al.

10th Biennial Congress and Exhibition of the International Stereotactic Radio surgery Society, Paris, France, May 8-12, 2011.

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An Efficient Segmentation Method for Ultrasound Images based on a Semi-supervised Approach and Patch-based Features

A.-R. Ciurte; N. Houhou; S. Nedevschi; A. Pica; F. Munier et al.

2011. 8th IEEE International Symposium on Biomedical Imaging, Chicago, Illinois, USA, March 30th - April 2nd, 2011. p. 969-972. DOI : 10.1109/ISBI.2011.5872564.

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Model-based Segmentation and Fusion of 3D Computed Tomography and 3D Ultrasound of the Eye for Radiotherapy Planning

M. Bach Cuadra; S. Gorthi; F. I. Karahanoglu; B. Paquier; A. Pica et al.

Computational Vision and Medical Image Processing; Springer, 2011. p. 247-263.

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Active Deformation Fields: Dense Deformation Field Estimation for Atlas-based Segmentation using the Active Contour Framework

S. Gorthi; V. Duay; X. Bresson; M. Bach Cuadra; S. Castro et al.

Medical Image Analysis. 2011. DOI : 10.1016/j.media.2011.05.008.

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Exporting Contours to DICOM-RTSTRUCT

S. Gorthi; M. Bach Cuadra; J.-P. Thiran

Kitware Newsletter.

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A post-processing pipeline to reconstruct the developing fetal brain using low-resolution MRI

M. Schaer; M. Bach Cuadra; S. Eliez; L. Guibaud; J.-P. Thiran

16th Annual Meeting of the Organization for Human Brain Mapping, Barcelona, Spain, June 6th-10th, 2010.

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Central and Cortical Gray Mater Segmentation of Magnetic Resonance Images of the Fetal Brain

M. Bach Cuadra; M. Schaer; G. V. Bonanno; A. André; L. Guibaud et al.

ISMRM-ESMRMB Joint Annual Meeting, Stockholm, Sweden, 1st-7th May, 2010.

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Regional cortical volumes and congenital heart disease: a MRI study in 22q11.2 deletion syndrome

M. Schaer; B. Glaser; M.-C. Ottet; M. Schneider; M. Bach Cuadra et al.

Journal of Neurodevelopmental Disorders. 2010. DOI : 10.1007/s11689-010-9061-4.

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Multi-Atlas based Segmentation of Head and Neck CT Images using Active Contour Framework

S. Gorthi; M. Bach Cuadra; U. Schick; P.-A. Tercier; A. S. Allal et al.

2010. MICCAI workshop on 3D Segmentation Challenge for Clinical Applications, Beijing, China, September 20-24, 2010.

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Deviant trajectories of cortical maturation in 22q11.2 deletion syndrome (22q11DS): A cross-sectional and longitudinal study

M. Schaer; M. Debbané; M. Bach Cuadra; M.-C. Ottet; B. Glaser et al.

Schizophrenia Research. 2009. DOI : 10.1016/j.schres.2009.09.016.

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Brain tissue segmentation of fetal MR images

M. Bach Cuadra; M. Schaer; A. Andre; L. Guibaud; S. Eliez et al.

2009. Workshop on Image Analysis for Developing Brain, in 12th International Conference on Medical Image Computing and Computer Assisted Intervention, Londond, UK, September 20-24, 2009.

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A multi-scale probabilistic atlas of the human connectome

Y. Aleman-Gomez; A. Griffa; J.-C. Houde; E. Najdenovska; S. Magon et al.

Scientific Data. 2022-08-23. DOI : 10.1038/s41597-022-01624-8.

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Through-Plane Super-Resolution With Autoencoders in Diffusion Magnetic Resonance Imaging of the Developing Human Brain

H. Kebiri; E. J. Canales-Rodriguez; H. Lajous; P. de Dumast; G. Girard et al.

Frontiers In Neurology. 2022-05-02. DOI : 10.3389/fneur.2022.827816.

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Editorial: Computational Neuroimage Analysis Tools for Brain (Diseases) Biomarkers

D. M. Sima; M. Bach Cuadra; T. B. Dyrby; K. Van Leemput

Frontiers In Neuroscience. 2022-02-18. DOI : 10.3389/fnins.2022.841807.

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Connectome Mapper 3: A Flexible and Open-Source Pipeline Software for Multiscale Multimodal Human Connectome Mapping

S. Tourbier; J. Rue Queralt; K. Glomb; Y. Aleman-Gomez; E. Mullier et al.

Journal of Open Source Software. 2022. DOI : 10.21105/joss.04248.

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Slice Estimation in Diffusion MRI of Neonatal and Fetal Brains in Image and Spherical Harmonics Domains Using Autoencoders

H. Kebiri; G. Girard; Y. Aleman-Gomez; T. Yu; A. Jakab et al.

2022-01-01. 13th International Workshop on Computational Diffusion MRI (CDMRI), Singapore, SINGAPORE, Sep 22, 2022. p. 3-13. DOI : 10.1007/978-3-031-21206-2_1.

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BMAT: An open-source BIDS managing and analysis tool

C. Vanden Bulcke; M. Wynen; J. Detobel; F. La Rosa; M. Absinta et al.

Neuroimage-Clinical. 2022-01-01. DOI : 10.1016/j.nicl.2022.103252.

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Combining Model Driven and Data Driven Approaches for Inverse Problems in Parameter Estimation and Image Reconstruction: From Modelling to Validation

T. Yu / J.-P. Thiran; M. Bach Cuadra (Dir.)

Lausanne, EPFL, 2022. DOI : 10.5075/epfl-thesis-9693.

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Deep learning-based analysis of multiple sclerosis lesions with high and ultra-high field MRI

F. La Rosa / J.-P. Thiran; M. Bach Cuadra (Dir.)

Lausanne, EPFL, 2022. DOI : 10.5075/epfl-thesis-9571.

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Automated detection of cortical lesions with single and multi-contrast 7T MRI

F. La Rosa; E. S. Beck; J. Maranzano; J. -P. Thiran; C. Granziera et al.

2021-10-01. p. 458-459.

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Cortical lesion detection using FLAWS in multiple sclerosis

J. Muller; R. Rahmanzadeh; C. Tsagkas; M. Barakovic; P. -J. Lu et al.

2021-10-01. p. 433-434.

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An assessment of intra-scanner reproducibility of myelin-sensitive MRI measures

R. Rahmanzadeh; M. Weigel; P. -J. Lu; L. Melie-Garcia; T. D. Nguyen et al.

2021-10-01. p. 430-431.

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CLaiMS-Net: cortical lesions assessment in multiple sclerosis patients via a convolutional neural network and a single 3T MRI acquisition

F. La Rosa; P. -J. Lu; R. Rahmanzadeh; A. Cagol; M. Barakovic et al.

2021-10-01. p. 457-458.

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Chronic White Matter Inflammation and Serum Neurofilament Levels in Multiple Sclerosis

P. Maggi; J. Kuhle; S. Schadelin; F. van der Meer; M. Weigel et al.

Neurology. 2021-08-10. DOI : 10.1212/WNL.0000000000012326.

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Fetal Brain Biometric Measurements on 3D Super-Resolution Reconstructed T2-Weighted MRI: An Intra- and Inter-observer Agreement Study

M. Khawam; P. de Dumast; P. Deman; H. Kebiri; T. Yu et al.

Frontiers In Pediatrics. 2021-08-10. DOI : 10.3389/fped.2021.639746.

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An automatic multi-tissue human fetal brain segmentation benchmark using the Fetal Tissue Annotation Dataset

K. Payette; P. de Dumast; H. Kebiri; I. Ezhov; J. C. Paetzold et al.

Scientific Data. 2021-07-06. DOI : 10.1038/s41597-021-00946-3.

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Myelin and axon pathology in multiple sclerosis assessed by myelin water and multi-shell diffusion imaging

R. Rahmanzadeh; P.-J. Lu; M. Barakovic; M. Weigel; P. Maggi et al.

Brain. 2021-06-01. DOI : 10.1093/brain/awab088.

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Automated assessment of paramagnetic rim lesions in multiple sclerosis patients with 3T and 7T MP2RAGE

F. La Rosa; G. Barquero; O. Al-Louzi; B. M. Maréchal Mortamet; T. Kober et al.

2021-05-15. The 2021 ISMRM & SMRT Annual Meeting & Eshibition, [Online], 15-20 may, 2021.

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GAMER-MRI in Multiple Sclerosis Identifies the Diffusion-Based Microstructural Measures That Are Most Sensitive to Focal Damage: A Deep-Learning-Based Analysis and Clinico-Biological Validation

P.-J. Lu; M. Barakovic; M. Weigel; R. Rahmanzadeh; R. Galbusera et al.

Frontiers In Neuroscience. 2021-04-06. DOI : 10.3389/fnins.2021.647535.

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MPRAGE to MP2RAGE UNI translation via generative adversarial network improves the automatic tissue and lesion segmentation in multiple sclerosis patients

F. La Rosa; T. Yu; G. Barquero; J.-P. Thiran; C. Granziera et al.

Computers in Biology and Medicine. 2021-02-26. DOI : 10.1016/j.compbiomed.2021.104297.

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Simulated Half-Fourier Acquisitions Single-shot Turbo Spin Echo (HASTE) of the Fetal Brain: Application to Super-Resolution Reconstruction

H. Lajous; T. Hilbert; C. W. Roy; S. Tourbier; P. de Dumast et al.

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Quantitative Evaluation of Enhanced Multi-plane Clinical Fetal Diffusion MRI with a Crossing-Fiber Phantom

H. Kebiri; H. Lajous; Y. Aleman-Gomez; G. Girard; E. C. Rodriguez et al.

2021-01-01. 12th International Workshop on Computational Diffusion MRI (CDMRI), ELECTR NETWORK, Oct 01, 2021. p. 12-22. DOI : 10.1007/978-3-030-87615-9_2.

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GAMER MRI: Gated-attention mechanism ranking of multi-contrast MRI in brain pathology

P.-J. Lu; Y. Yoo; R. Rahmanzadeh; R. Galbusera; M. Weigel et al.

Neuroimage-Clinical. 2021-01-01. DOI : 10.1016/j.nicl.2020.102522.

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Model-informed machine learning for multi-component T2 relaxometry

T. Yu; E. J. Canales Rodriguez; M. Pizzolato; G. F. Piredda; T. Hilbert et al.

Medical Image Analysis. 2020-12-17. DOI : 10.1016/j.media.2020.101940.

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A step forward toward the fully automated assessment of the central vein sign

M. J. Fartaria; O. Al-Louzi; T. Huelnhagen; L. Daboul; P. Maggi et al.

2020-12-01. 8th Joint ACTRIMS-ECTRIMS Meeting (MSVirtual), ELECTR NETWORK, Sep 11-13, 2020. p. 7-7.

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Rimnet: a deep 3D multimodal MRI architecture for paramagnetic rim lesions assessment in multiple sclerosis

G. Barquero; F. La Rosa; H. Kebiri; P. -J. Lu; R. Rahmanzadeh et al.

2020-12-01. 8th Joint ACTRIMS-ECTRIMS Meeting (MSVirtual), ELECTR NETWORK, Sep 11-13, 2020. p. 36-36.

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Quantitative susceptibility mapping classifies white matter lesions with different myelin and axonal content and quantifies diffuse pathology in MS

R. Rahmanzadeh; P. -J. Lu; M. Barakovic; M. Weigel; T. D. Nguyen et al.

2020-12-01. 8th Joint ACTRIMS-ECTRIMS Meeting (MSVirtual), ELECTR NETWORK, Sep 11-13, 2020. p. 29-30.

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Studying intralesional axonal damage in ms white matter lesions with diffusion mri biophysical models

M. Barakovic; R. Rahmanzadeh; P. -J. Lu; P. Maggi; M. Absinta et al.

2020-12-01. 8th Joint ACTRIMS-ECTRIMS Meeting (MSVirtual), ELECTR NETWORK, Sep 11-13, 2020. p. 426-427.

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Advanced magnetic resonance imaging for myelin and axonal density in ms: correlation with clinical disability and serum neurofilament levels

R. Rahmanzadeh; P. -J. Lu; M. Barakovic; M. Weigel; S. Schaedelin et al.

2020-12-01. 8th Joint ACTRIMS-ECTRIMS Meeting (MSVirtual), ELECTR NETWORK, Sep 11-13, 2020. p. 372-372.

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Translating mprage to mp2rage improves the automatic tissue and lesion segmentation in multiple sclerosis patients

F. La Rosa; T. Yu; G. Barquero; J. -P. Thiran; C. Granziera et al.

2020-12-01. 8th Joint ACTRIMS-ECTRIMS Meeting (MSVirtual), ELECTR NETWORK, Sep 11-13, 2020. p. 125-126.

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Evolution of Cortical and White Matter Lesion Load in Early-Stage Multiple Sclerosis: Correlation With Neuroaxonal Damage and Clinical Changes

R.-A. Todea; P.-J. Lu; M. J. Fartaria; G. Bonnier; R. Du Pasquier et al.

Frontiers In Neurology. 2020-09-04. DOI : 10.3389/fneur.2020.00973.

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RimNet: A deep 3D multimodal MRI architecture for paramagnetic rim lesion assessment in multiple sclerosis

G. Barquero; F. La Rosa; H. Kebiri; P.-J. Lu; R. Rahmanzadeh et al.

NeuroImage: Clinical. 2020-09-04. DOI : 10.1016/j.nicl.2020.102412.

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Partial-volume modeling reveals reduced gray matter in specific thalamic nuclei early in the time course of psychosis and chronic schizophrenia

Y. Aleman-Gomez; E. Najdenovska; T. Roine; M. J. Fartaria; E. J. Canales-Rodriguez et al.

Human Brain Mapping. 2020-07-10. DOI : 10.1002/hbm.25108.

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Multiple sclerosis cortical and WM lesion segmentation at 3T MRI: a deep learning method based on FLAIR and MP2RAGE

F. La Rosa; A. Abdulkadir; M. J. Fartaria; R. Rahmanzadeh; P.-J. Lu et al.

NeuroImage: Clinical. 2020-06-30. DOI : 10.1016/j.nicl.2020.102335.

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Normalization of aberrant pretherapeutic dynamic functional connectivity of extrastriate visual system in patients who underwent thalamotomy with stereotactic radiosurgery for essential tremor: a resting-state functional MRI study

C. Tuleasca; T. A. W. Bolton; J. Regis; E. Najdenovska; T. Witjas et al.

Journal Of Neurosurgery. 2020-06-01. DOI : 10.3171/2019.2.JNS183454.

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Higher Order Spherical Harmonics Reconstruction of Fetal Diffusion MRI With Intensity Correction

M. Deprez; A. Price; D. Christiaens; G. L. Estrin; L. Cordero-Grande et al.

Ieee Transactions On Medical Imaging. 2020-04-01. DOI : 10.1109/TMI.2019.2943565.

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CVSnet: A machine learning approach for automated central vein sign assessment in multiple sclerosis

P. Maggi; M. J. Fartaria; J. Jorge; F. La Rosa; M. Absinta et al.

Nmr In Biomedicine. 2020-03-03. DOI : 10.1002/nbm.4283.

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Improved susceptibility-weighted imaging for high contrast and resolution thalamic nuclei mapping at 7T

J. Jorge; F. Gretsch; E. Najdenovska; C. Tuleasca; M. Levivier et al.

Magnetic Resonance In Medicine. 2020-02-12. DOI : 10.1002/mrm.28197.

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Quantification in Musculoskeletal Imaging Using Computational Analysis and Machine Learning: Segmentation and Radiomics

M. B. Cuadra; P. Omoumi

Seminars In Musculoskeletal Radiology. 2020-02-01. DOI : 10.1055/s-0039-3400268.

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Resting-state functional MRI for functional neurosurgery: seeing the light?

C. Tuleasca; J. Regis; E. Najdenovska; T. Witjas; N. Girard et al.

Journal Of Neurosurgery. 2019-10-01. DOI : 10.3171/2019.1.JNS1995.

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Deep learning-based detection of cortical lesions in multiple sclerosis patients with FLAIR, DIR, and MP2RAGE MRI sequences

F. La Rosa; M. J. Fartaria; A. Abdulkadir; R. Rahmanzadeh; P.-J. Lu et al.

2019-09-10. 35th Congress of the European-Committee-for-Treatment-and-Research-in-Multiple-Sclerosis (ECTRIMS), Stockholm, Sweden, September 11-13, 2019. p. 131-356. DOI : 10.1177/1352458519868078.

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Deep learning analysis applied to multi-parametric advanced MRI shows higher myelin content and neurite density in juxtacortical lesions compared to periventricular lesions

P. -J. Lu; R. Rahmanzadeh; R. Galbusera; B. Odry; M. Weigel et al.

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A fully automated approach for differential diagnosis support in multiple sclerosis based on the central vein sign

M. J. Fartaria; P. Maggi; P. Sati; D. S. Reich; C. Granziera et al.

Notice détaillée

Deep learning-based detection of cortical lesions in multiple sclerosis patients with FLAIR, DIR, and MP2RAGE MRI sequences

F. La Rosa; M. J. Fartaria; A. Abdulkadir; R. Rahmanzadeh; P. -J. Lu et al.

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Axonal and myelin injury in white matter and cortex of relapsing-remitting and progressive multiple sclerosis patients: a combined myelin water and multi-shell diffusion MRI study

R. Rahmanzadeh; P. -J. Lu; M. Weigel; R. Galbusera; T. D. Nguyen et al.

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Axonal damage explains part of and extends beyond the diffuse pathology evidenced by T1 mapping in normal-appearing white matter of multiple sclerosis patients

R. Rahmanzadeh; P. -J. Lu; M. Weigel; R. Galbusera; F. La Rosa et al.

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Automated Detection and Segmentation of Multiple Sclerosis Lesions Using Ultra-High-Field MP2RAGE

M. J. Fartaria; P. Sati; A. Todea; E.-W. Radue; R. Rahmanzadeh et al.

Investigative Radiology. 2019-06-01. DOI : 10.1097/RLI.0000000000000551.

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Episodic memory decline in Parkinson' s disease: relation with white matter hyperintense lesions and influence of quantification method

V. Dunet; M. J. Fartaria; J. Deverdun; E. Le Bars; F. Maury et al.

Brain Imaging And Behavior. 2019-06-01. DOI : 10.1007/s11682-018-9909-x.

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A Novel Spatial-Angular Domain Regularisation Approach for Restoration of Diffusion MRI

A. Mella; A. Daducci; G. Orlandi; J.-P. Thiran; M. Deprez et al.

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Longitudinal analysis of white matter and cortical lesions in multiple sclerosis

M. J. Fartaria; T. Kober; C. Granziera; M. B. Cuadra

Neuroimage-Clinical. 2019-01-01. DOI : 10.1016/j.nicl.2019.101938.

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Letter: Deep Brain Stimulation of the Pedunculopontine Nucleus Area in Parkinson Disease: Magnetic Resonance Imaging- Based Anatomoclinical Correlations and Optimal Target

C. Tuleasca; J. Regis; E. Najdenovska; T. Witjas; N. Girard et al.

Neurosurgery. 2019-01-01. DOI : 10.1093/neuros/nyy516.

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Comparison of MRI-based automated segmentation methods and functional neurosurgery targeting with direct visualization of the Ventro-intermediate thalamic nucleus at 7T

E. Najdenovska; C. Tuleasca; J. Jorge; P. Maeder; J. P. Marques et al.

Scientific Reports. 2019. DOI : 10.1038/s41598-018-37825-8.

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Pretherapeutic resting-state fMRI profiles are associated with MR signature volumes after stereotactic radiosurgical thalamotomy for essential tremor

C. Tuleasca; J. Regis; E. Najdenovska; T. Witjas; N. Girard et al.

Journal Of Neurosurgery. 2018-12-01. DOI : 10.3171/2018.7.GKS18752.

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In-vivo probabilistic atlas of human thalamic nuclei based on diffusion-weighted magnetic resonance imaging

E. Najdenovska; Y. Aleman-Gomez; G. Battistella; M. Descoteaux; P. Hagmann et al.

Scientific Data. 2018-11-27. DOI : 10.1038/sdata.2018.270.

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Personalized Anatomic Eye Model From T1-Weighted Volume Interpolated Gradient Echo Magnetic Resonance Imaging of Patients With Uveal Melanoma

H.-G. Nguyen; R. Sznitman; P. Maeder; A. Schalenbourg; M. Peroni et al.

International Journal Of Radiation Oncology Biology Physics. 2018-11-15. DOI : 10.1016/j.ijrobp.2018.05.004.

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Accuracy versus reproducibility: comprehensive assessment of four automated methods for multiple sclerosis lesion segmentation

M. J. Fartaria; R. Corredor-Jerez; J. Richiardi; B. Marechal; C. Granziera et al.

2018-10-01. 34th Congress of the European-Committee-for-Treatment-and-Research-in-Multiple-Sclerosis (ECTRIMS), Berlin, GERMANY, Oct 10-12, 2018. p. 359-359.

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Automated assessment of new and enlarged white matter and cortical lesions in early multiple sclerosis

M. J. Fartaria; G. Bonnier; T. Kober; M. B. Cuadra; C. Granziera

2018-10-01. 34th Congress of the European-Committee-for-Treatment-and-Research-in-Multiple-Sclerosis (ECTRIMS), Berlin, GERMANY, Oct 10-12, 2018. p. 570-570.

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Differential diagnosis of multiple sclerosis with machine learning-based central vein sign recognition

J. Richiardi; P. Maggi; M. J. Fartaria; F. La Rosa; J. Jorge et al.

2018-10-01. 34th Congress of the European-Committee-for-Treatment-and-Research-in-Multiple-Sclerosis (ECTRIMS), Berlin, GERMANY, Oct 10-12, 2018. p. 530-531.

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Shallow vs deep learning architectures for white matter lesion segmentation in the early stages of multiple sclerosis

F. La Rosa; M. J. Fartaria; T. Kober; J. Richiardi; C. Granziera et al.

2018-09-10. BrainLes Workshop, MICCAI 2018, Granada, Spain, September 16, 2018. DOI : 10.1007/978-3-030-11723-8_14.

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Ocular Structures Segmentation from Multi-sequences MRI Using 3D Unet with Fully Connected CRFs

Huu-Giao Nguyen; A. Pica; P. Maeder; A. Schalenbourg; M. Peroni et al.

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Visually-sensitive networks in essential tremor: evidence from structural and functional imaging

C. Tuleasca; J. Régis; E. Najdenovska; T. Witjas; N. Girard et al.

Brain. 2018. DOI : 10.1093/brain/awy094.

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Assessing the clinical outcome of Vim radiosurgery with voxel-based morphometry: visual areas are linked with tremor arrest!

C. Tuleasca; T. Witjas; E. Najdenovska; A. Verger; N. Girard et al.

Acta Neurochirurgica. 2017. DOI : 10.1007/s00701-017-3317-7.

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An Ultra-High Field Study of Cerebellar Pathology in Early Relapsing-Remitting Multiple Sclerosis Using MP2RAGE

M. J. Fartaria; K. O'Brien; A. Sorega; G. Bonnier; A. Roche et al.

Investigative Radiology. 2017. DOI : 10.1097/Rli.0000000000000338.

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Automatic Segmentation of the Eye in 3D Magnetic Resonance Imaging: A Novel Statistical Shape Model for Treatment Planning of Retinoblastoma

C. Ciller; S. I. De Zanet; M. B. Rueegsegger; A. Pica; R. Sznitman et al.

International Journal Of Radiation Oncology Biology Physics. 2015. DOI : 10.1016/j.ijrobp.2015.02.056.

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A Multi-Contrast MRI Study of Microstructural Brain Damage in Patients with Mild Cognitive Impairment

C. Granziera; A. Daducci; A. Donati; G. Bonnier; D. Romascano et al.

NeuroImage: Clinical. 2015. DOI : 10.1016/j.nicl.2015.06.003.

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Landmark Detection for Fusion of Fundus and MRI Toward a Patient-Specific Multimodal Eye Model

S. I. De Zanet; C. Ciller; T. Rudolph; P. Maeder; F. Munier et al.

Ieee Transactions On Biomedical Engineering. 2015. DOI : 10.1109/Tbme.2014.2359676.

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An evaluation of volume-based morphometry for prediction of mild cognitive impairment and Alzheimer's disease

D. Schmitter; A. Roche; B. Maréchal; D. Ribes; A. Abdulkadir et al.

NeuroImage: Clinical. 2015. DOI : 10.1016/j.nicl.2014.11.001.

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Volume-based vs. voxel-based brain morphometry in Alzheimer's disease prediction

A. Roche; D. A. Schmitter; B. M. Maréchal Mortamet; D. Ribes Lemay; A. Abdulkadir et al.

2014. 23rd International Society for Magnetic Resonance in Medicine (ISMRM) Conference, Milan, Italy, May 10-16, 2014.

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Semi-Supervised Segmentation of Ultrasound Images Based on Patch Representation and Continuous Min Cut

A. Ciurte; X. Bresson; O. Cuisenaire; N. Houhou; S. Nedevschi et al.

Plos One. 2014. DOI : 10.1371/journal.pone.0100972.

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MBIS: Multivariate Bayesian Image Segmentation tool

O. Esteban; G. Wollny; S. Gorthi; M.-J. Ledesma-Carbayo; J.-P. Thiran et al.

Computer Methods And Programs In Biomedicine. 2014. DOI : 10.1016/j.cmpb.2014.03.003.

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Evaluation and Comparison of Current Fetal Ultrasound Image Segmentation Methods for Biometric Measurements: A Grand Challenge

S. Rueda; S. Fathima; C. L. Knight; M. Yaqub; A. T. Papageorghiou et al.

Ieee Transactions On Medical Imaging. 2014. DOI : 10.1109/Tmi.2013.2276943.

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Simulation-based evaluation of susceptibility distortion correction methods in diffusion MRI for connectivity analysis

O. Esteban; A. Daducci; E. Caruyer; K. O'Brien; L. Carbayo et al.

2014. IEEE 11th International Symposium on Biomedical Imaging - From Nano to Macro (ISBI), Beijing, China, April 29 - May 2, 2014. p. 738-741. DOI : 10.1109/ISBI.2014.6867976.

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A NEW APPROACH FOR CEREBELLO-THALAMIC MOTOR NETWORK EVALUATION IN ASYMPTOMATIC PREMUTATION CARRIERS AT RISK FOR FXTAS

G. Battistella; N. Ghazaleh; E. Fornari; E. Najdenovska; M. Bach Cuadra et al.

Human Brain Mapping, Seattle, USA, June 16-20, 2013.

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Weighted Shape-Based Averaging With Neighborhood Prior Model for Multiple Atlas Fusion-Based Medical Image Segmentation

S. Gorthi; M. Bach Cuadra; P.-A. Tercier; A. S. Allal; J.-P. Thiran

IEEE Signal Processing Letters. 2013. DOI : 10.1109/LSP.2013.2279269.

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Multi Atlas Fusion Methods for Medical Image Segmentation

S. Venkata Ravi Mohana Sai Gorthi / J.-P. Thiran (Dir.)

Lausanne, EPFL, 2013. DOI : 10.5075/epfl-thesis-5747.

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Towards a connectome mapping pipeline for neonates using high-resolution MP2RAGE and DTI

A. Pauli; J. Schneider; M. Bach Cuadra; A. Griffa; E. Fischi Gomez et al.

2013. 21st Annual Meeting International Society for Magnetic Resonance in Medicine, Salt Lake City, Utah, USA, April 20-26,2013.

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Multi-atlas fusion methods for segmentation of head and neck lymph nodes for radiotherapy planning

S. Gorthi; M. Bach Cuadra; J. Villafruela Vicario; P.-A. Tercier; J.-P. Thiran et al.

2013. 2nd ESTRO Forum, Geneva, April 19-23, 2013.

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Atlas-free brain tissue segmentation using a single T1-weighted MRI acquisition

T. Kober; A. Roche; O. Esteban-Sanz; S. Gorthi; D. Ribes et al.

2012. International Society for Magnetic Resonance in Medicine (ISMRM), Melbourne, Australia, May 5-11.

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STATISTICAL MODELING OF THE EYE FOR MULTIMODAL TREATMENT PLANNING FOR EXTERNAL BEAM RADIOTHERAPY OF INTRAOCULAR TUMORS

M. RUEEGSEGGER; M. Bach Cuadra; A. Pica; C. AMSTUTZ; T. RUDOLPH et al.

International Journal of Radiation Oncology, Biology, Physics.. 2012. DOI : 10.1016/j.ijrobp.2012.05.040.

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Brain tissue segmentation on diffusion weighted magnetic resonance data

O. Esteban-Sanz; S. Gorthi; G. Wollny; A. Daducci; M. J. Ledesma-Carbayo et al.

2012. IEEE International Symposium on Biomedical Imaging (ISBI) 2012, Barcelona, Spain, 2-5 May 2012.

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Evaluation of Atlas Fusion Strategies for Segmentation of Head and Neck Lymph Nodes for Radiotherapy Planning

S. Gorthi; M. Bach Cuadra; U. Schick; P.-A. Tercier; A. S. Allal et al.

2012. IEEE International Symposium on Biomedical Imaging (ISBI), Barcelona, Spain, May 2-5, 2012. p. 1276-1279. DOI : 10.1109/ISBI.2012.6235795.

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How to Measure Cortical Folding from MR Images: a Step-by-Step Tutorial to Compute Local Gyrification Index

M. Schaer; M. Bach Cuadra; N. Schmansky; B. Fischl; J.-P. Thiran et al.

Journal of Visualized Experiments. 2012. DOI : 10.3791/3417.

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A pipeline approach with spatial information for segmenting multiple sclerosis lesions on brain magnetic resonance imaging

M. Cabezas Grebol; M. Bach Cuadra; A. Oliver; X. Lladó; J. Freixenet et al.

5th Joint triennial congress of the European and Americas committees for treatment and research in multiple sclerosis, Amsterdam, The Netherlands, October 19-22, 2011.

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Fusion of Multi-Atlas Segmentations with Spatial Distribution Modeling

S. Gorthi; M. Bach Cuadra; U. Schick; P.-A. Tercier; A. S. Allal et al.

2011. MICCAI Worskshop on Multi-Atlas Labeling and Statistical Fusion, Toronto, Canada, September, 18-22, 2011.

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On the Convergence of EM-Like Algorithms for Image Segmentation using Markov Random Fields

A. Roche; D. Ribes; M. Bach Cuadra; G. Krüger

Medical Image Analysis -Elsevier-. 2011. DOI : 10.1016/j.media.2011.05.002.

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Towards a diffusion image processing validation and accuracy prediction framework

F. Pizzorni Ferrarese; A. Daducci; M. Bach Cuadra; A. Lemkaddem; C. Granziera et al.

2011. IEEE International Conference on Image Processing, Brussel, Belgium, September 11-14, 2011. p. 2269-2272. DOI : 10.1109/ICIP.2011.6116091.

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Comparison of Energy Minimization Methods for 3-D Brain Tissue Classification

S. Gorthi; J.-P. Thiran; M. Bach Cuadra

2011. IEEE International Conference on Image Processing, Brussels, Belgium, September 11-14, 2011. p. 57-60. DOI : 10.1109/ICIP.2011.6116615.

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Review on Atlas-based Segmentation of Magnetic Resonance Brain Images

M. Cabezas Grebol; A. Oliver; X. Llado; J. Freixenet; M. Bach Cuadra

Computer Methods and Programs in Biomedicine. 2011. DOI : 10.1016/j.cmpb.2011.07.015.

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Comparison of tissue classification models for automatic brain MR segmentation

D. Ribes; B. Mortamet; M. Bach Cuadra; C. Jack; R. Meuli et al.

19th Annual Meeting and Exhibition ISMRM, Montreal, Quebec, Canada, May 7-13, 2011.

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Quantitative morphometry analysis of the fetal brain using clinical MR imaging

M. Bach Cuadra; G. V. Bonanno; L. Guibaud; S. Eliez; J.-P. Thiran et al.

19th Annual Meeting and Exhibition ISMRM, Montreal, Quebec, Canada, May 7-13.

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3D Ultrasound Tumor Segmentation and Fusion with CT for Stereotactic Radiation Therapy Planning of Retinoblastoma

A. Pica; F. I. Karahanoglu; A.-R. Ciurte; S. Gorthi; A. Balmer et al.

10th Biennial Congress and Exhibition of the International Stereotactic Radio surgery Society, Paris, France, May 8-12, 2011.

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An Efficient Segmentation Method for Ultrasound Images based on a Semi-supervised Approach and Patch-based Features

A.-R. Ciurte; N. Houhou; S. Nedevschi; A. Pica; F. Munier et al.

2011. 8th IEEE International Symposium on Biomedical Imaging, Chicago, Illinois, USA, March 30th - April 2nd, 2011. p. 969-972. DOI : 10.1109/ISBI.2011.5872564.

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Model-based Segmentation and Fusion of 3D Computed Tomography and 3D Ultrasound of the Eye for Radiotherapy Planning

M. Bach Cuadra; S. Gorthi; F. I. Karahanoglu; B. Paquier; A. Pica et al.

Computational Vision and Medical Image Processing; Springer, 2011. p. 247-263.

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Active Deformation Fields: Dense Deformation Field Estimation for Atlas-based Segmentation using the Active Contour Framework

S. Gorthi; V. Duay; X. Bresson; M. Bach Cuadra; S. Castro et al.

Medical Image Analysis. 2011. DOI : 10.1016/j.media.2011.05.008.

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Exporting Contours to DICOM-RTSTRUCT

S. Gorthi; M. Bach Cuadra; J.-P. Thiran

Kitware Newsletter.

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A post-processing pipeline to reconstruct the developing fetal brain using low-resolution MRI

M. Schaer; M. Bach Cuadra; S. Eliez; L. Guibaud; J.-P. Thiran

16th Annual Meeting of the Organization for Human Brain Mapping, Barcelona, Spain, June 6th-10th, 2010.

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Central and Cortical Gray Mater Segmentation of Magnetic Resonance Images of the Fetal Brain

M. Bach Cuadra; M. Schaer; G. V. Bonanno; A. André; L. Guibaud et al.

ISMRM-ESMRMB Joint Annual Meeting, Stockholm, Sweden, 1st-7th May, 2010.

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Regional cortical volumes and congenital heart disease: a MRI study in 22q11.2 deletion syndrome

M. Schaer; B. Glaser; M.-C. Ottet; M. Schneider; M. Bach Cuadra et al.

Journal of Neurodevelopmental Disorders. 2010. DOI : 10.1007/s11689-010-9061-4.

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Multi-Atlas based Segmentation of Head and Neck CT Images using Active Contour Framework

S. Gorthi; M. Bach Cuadra; U. Schick; P.-A. Tercier; A. S. Allal et al.

2010. MICCAI workshop on 3D Segmentation Challenge for Clinical Applications, Beijing, China, September 20-24, 2010.

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Deviant trajectories of cortical maturation in 22q11.2 deletion syndrome (22q11DS): A cross-sectional and longitudinal study

M. Schaer; M. Debbané; M. Bach Cuadra; M.-C. Ottet; B. Glaser et al.

Schizophrenia Research. 2009. DOI : 10.1016/j.schres.2009.09.016.

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Brain tissue segmentation of fetal MR images

M. Bach Cuadra; M. Schaer; A. Andre; L. Guibaud; S. Eliez et al.

2009. Workshop on Image Analysis for Developing Brain, in 12th International Conference on Medical Image Computing and Computer Assisted Intervention, Londond, UK, September 20-24, 2009.

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Enseignement & Phd

A dirigé les thèses EPFL de

La Rosa Francesco , Yu Thomas ,