Meritxell Bach Cuadra

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Scientist

meritxell.bach@epfl.ch +41 21 693 48 07 https://www.unil.ch/mial/home/menuinst/people/meritxell-bach-cuadra.html

EPFL STI IEL LTS5
ELD 233 (Bâtiment ELD)
Station 11
CH-1015 Lausanne

+41 21 693 48 07
Office: ELD 233
EPFL > STI > IEM > LTS5

Web site: Web site: https://lts5www.epfl.ch/

EPFL CIBM-SP
CH F0 622 (Bâtiment CH)
Station 6
CH-1015 Lausanne

+41 21 693 48 07
Office: ELD 233
EPFL > VPA > VPA-AVP-CP > CIBM > CIBM-SP

Web site: Web site: https://www.cibm.ch/

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Biography

Meritxell Bach Cuadra received her degree in Telecommunication Engineering (ETSETB) from the Universitat Politècnica de Catalunya (UPC), Spain, in September 1999. In December 1999, she joined the Computer Vision and Image Analysis Group at the Signal Processing Laboratory (LTS5) as a Ph.D. student under the supervision of Prof. Jean-Philippe Thiran. She obtained her PhD degree in November 2003 for her work "Atlas-based Segmentation and Classification of Magnetic Resonance Brain Images." In June 2005 she joined the Signal Processing Core (SPC) of the Biomedical Imaging Center (CIBM) as responsible of the SPC-CHUV Unit at the Radiology Department of the Lausanne University Hospital (CHUV). As head of the SPC-CHUV unit her goal is to coordinate the medical image analysis research at LTS5 with the needs of expertise in signal/image processing of physicians and researchers at CHUV. In March 2011 Meritxell was promoted to Senior Lecturer (Maître dEnseignement et de Recherche) at the School of Biology and Medicine of the University of Lausanne where she will teach and develop independent researches at the interface between medical Imaging and image analysis. She is currently affiliated to both the Radiology Department of the Lausanne University Hospital and to the Signal Processing Laboratory LTS5 of the EPFL. Her main research interests are related to quantitative analysis of medical imaging and the integration of prior knowledge in this analysis. Meritxells research is focus to: - Segmentation (Active Contours, Graph theory), - Statistical classification (Bayesian framework, Hidden Markov Random Fields) - Image registration - applied to different medical image modalities like Magnetic Resonance (MR) and Diffusion MR imaging, Ultrasound imaging and Computed Tomography.

Publications

Infoscience publications

Infoscience

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.

Meritxell Bach Cuadra

Scientist

Biography

Publications

Infoscience publications

Infoscience

A multi-scale probabilistic atlas of the human connectome

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

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

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

BMAT: An open-source BIDS managing and analysis tool

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

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

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

Cortical lesion detection using FLAWS in multiple sclerosis

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

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

Chronic White Matter Inflammation and Serum Neurofilament Levels in Multiple Sclerosis

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

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

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

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

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

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

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

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

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

Model-informed machine learning for multi-component T2 relaxometry

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Longitudinal analysis of white matter and cortical lesions in multiple sclerosis

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

MBIS: Multivariate Bayesian Image Segmentation tool

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

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

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

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

Multi Atlas Fusion Methods for Medical Image Segmentation

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