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08/31/2023
Improving Multiple Sclerosis Lesion Segmentation Across Clinical Sites: A Federated Learning Approach with Noise-Resilient Training
Accurately measuring the evolution of Multiple Sclerosis (MS) with magne...
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10/31/2022
TW-BAG: Tensor-wise Brain-aware Gate Network for Inpainting Disrupted Diffusion Tensor Imaging
Diffusion Weighted Imaging (DWI) is an advanced imaging technique common...
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05/03/2022
MS Lesion Segmentation: Revisiting Weighting Mechanisms for Federated Learning
Federated learning (FL) has been widely employed for medical image analy...
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01/17/2019
Multiple Sclerosis Lesion Synthesis in MRI using an encoder-decoder U-NET
In this paper, we propose generating synthetic multiple sclerosis (MS) l...
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11/05/2018
Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge
Gliomas are the most common primary brain malignancies, with different d...
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10/04/2018
Survival prediction using ensemble tumor segmentation and transfer learning
Segmenting tumors and their subregions is a challenging task as demonstr...
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05/31/2018
One-shot domain adaptation in multiple sclerosis lesion segmentation using convolutional neural networks
In recent years, several convolutional neural network (CNN) methods have...
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01/19/2018
Quantitative analysis of patch-based fully convolutional neural networks for tissue segmentation on brain magnetic resonance imaging
Accurate brain tissue segmentation in Magnetic Resonance Imaging (MRI) h...
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09/26/2017