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

Publications associées (35)

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Development and clinical validation of computational imaging biomarkers for neurodegenerative diseases

Veronica Lily Ravano

Neurodegenerative and neuroinflammatory disorders often involve complex pathophysiological mechanisms that are â to this date â only partially understood. A more comprehensive understanding of those microstructural processes and their characterization ...

EPFL2024

SAGTTA: SALIENCY GUIDED TEST TIME AUGMENTATION FOR MEDICAL IMAGE SEGMENTATION ACROSS VENDOR DOMAIN SHIFT

Devavrat Tomar

Test time augmentation has been shown to be an effective approach to combat domain shifts in deep learning. Despite their promising performance levels, the interpretability of the underlying used models is however low. Saliency maps have been widely used i ...

New York2023

Automated neuron tracking inside moving and deforming C. elegans using deep learning and targeted augmentation

Sahand Jamal Rahi, Kseniia Korchagina

Reading out neuronal activity from three-dimensional (3D) functional imaging requires segmenting and tracking individual neurons. This is challenging in behaving animals if the brain moves and deforms. The traditional approach is to train a convolutional n ...

Berlin2023

Objectives: The precise location of multiple sclerosis (MS) cortical lesions can be very challenging at 3 T, yet distinguishing them from subcortical lesions is essential for the diagnosis and prognosis of the disease. Compressed sensing-accelerated fluid ...

LIPPINCOTT WILLIAMS & WILKINS2023

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

Francesco La Rosa

Multiple sclerosis (MS) is the most common demyelinating disease of the central nervous system and affects almost 3 million people worldwide. There is currently no cure for MS, and its symptoms, starting with fatigue and weakness, often progress over time ...

EPFL2022

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The presence of cortical lesions in multiple sclerosis patients has emerged as an important biomarker of the disease. They appear in the earliest stages of the illness and have been shown to correlate with the severity of clinical symptoms. However, cortic ...

2020

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Objectives The aim of this study was to develop a new automated segmentation method of white matter (WM) and cortical multiple sclerosis (MS) lesions visible on magnetization-prepared 2 inversion-contrast rapid gradient echo (MP2RAGE) images acquired at 7 ...

LIPPINCOTT WILLIAMS & WILKINS2019

Brain tissue segmentation based on MP2RAGE multi-contrast images in 7 T MRI

Tobias Kober

We proposed a method for segmentation of brain tissues-gray matter, white matter, and cerebrospinal fluid-using multi-contrast images, including a T1 map and a uniform T1-weighted image, from a magnetization-prepared 2 rapid acquisition gradient echoes (MP ...

PUBLIC LIBRARY SCIENCE2019

Longitudinal analysis of white matter and cortical lesions in multiple sclerosis

Meritxell Bach Cuadra, Tobias Kober, Cristina Granziera, Mario Joao Fartaria de Oliveira

Purpose: The goals of this study were to assess the performance of a novel lesion segmentation tool for longitudinal analyses, as well as to validate the generated lesion progression map between two time points using conventional and non-conventional MR se ...

2019

Efficient Active Learning for Image Classification and Segmentation using a Sample Selection and Conditional Generative Adversarial Network

Jean-Philippe Thiran

Training robust deep learning (DL) systems for medical image classification or segmentation is challenging due to limited images covering different disease types and severity. We propose an active learning (AL) framework to select most informative samples ...

Springer2018