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相关论文: Multiple Sclerosis Lesion Activity Segmentation wi…

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Objective: Multiple Sclerosis (MS) is an autoimmune, and demyelinating disease that leads to lesions in the central nervous system. This disease can be tracked and diagnosed using Magnetic Resonance Imaging (MRI). Up to now a multitude of…

图像与视频处理 · 电气工程与系统科学 2022-01-07 Mehdi SadeghiBakhi , Hamidreza Pourreza , Hamidreza Mahyar

Lesion segmentation is a core task for quantitative analysis of MRI scans of Multiple Sclerosis patients. The recent success of deep learning techniques in a variety of medical image analysis applications has renewed community interest in…

图像与视频处理 · 电气工程与系统科学 2020-12-29 Huahong Zhang , Ipek Oguz

Multiple Sclerosis (MS) is an autoimmune disease that leads to lesions in the central nervous system. Magnetic resonance (MR) images provide sufficient imaging contrast to visualize and detect lesions, particularly those in the white…

计算机视觉与模式识别 · 计算机科学 2018-03-28 Snehashis Roy , John A. Butman , Daniel S. Reich , Peter A. Calabresi , Dzung L. Pham

Multiple sclerosis (MS) is a chronic inflammatory and degenerative disease of the central nervous system, characterized by the appearance of focal lesions in the white and gray matter that topographically correlate with an individual…

计算机视觉与模式识别 · 计算机科学 2022-01-31 Yang Ma , Chaoyi Zhang , Mariano Cabezas , Yang Song , Zihao Tang , Dongnan Liu , Weidong Cai , Michael Barnett , Chenyu Wang

Introduction: Multiple Sclerosis (MS) is a chronic disease that affects millions of people across the globe. MS can critically affect different organs of the central nervous system such as the eyes, the spinal cord, and the brain.…

图像与视频处理 · 电气工程与系统科学 2023-02-21 Atif Shah , Maged S. Al-Shaibani , Moataz Ahmad , Reem Bunyan

Multiple sclerosis lesion activity segmentation is the task of detecting new and enlarging lesions that appeared between a baseline and a follow-up brain MRI scan. While deep learning methods for single-scan lesion segmentation are common,…

计算机视觉与模式识别 · 计算机科学 2020-06-02 Nils Gessert , Marcel Bengs , Julia Krüger , Roland Opfer , Ann-Christin Ostwaldt , Praveena Manogaran , Sven Schippling , Alexander Schlaefer

Magnetic resonance imaging is a fundamental tool to reach a diagnosis of multiple sclerosis and monitoring its progression. Although several attempts have been made to segment multiple sclerosis lesions using artificial intelligence, fully…

Segmentation of white matter lesions and deep grey matter structures is an important task in the quantification of magnetic resonance imaging in multiple sclerosis. In this paper we explore segmentation solutions based on convolutional…

In this paper, we present an automated approach for segmenting multiple sclerosis (MS) lesions from multi-modal brain magnetic resonance images. Our method is based on a deep end-to-end 2D convolutional neural network (CNN) for slice-based…

计算机视觉与模式识别 · 计算机科学 2019-04-09 Shahab Aslani , Michael Dayan , Loredana Storelli , Massimo Filippi , Vittorio Murino , Maria A Rocca , Diego Sona

Multiple Sclerosis (MS) is a chronic autoimmune disease that can significantly reduce the quality of life of a patient. Existing treatment options can only help slow down the progression of the disease. Therefore, early detection and…

计算机视觉与模式识别 · 计算机科学 2026-05-12 Abdul Basit , Ashir Rashid , Muhammad Abdullah Hanif , Muhammad Shafique

Cortical lesions (CLs) have emerged as valuable biomarkers in multiple sclerosis (MS), offering high diagnostic specificity and prognostic relevance. However, their routine clinical integration remains limited due to subtle magnetic…

Multiple Sclerosis (MS) is a severe neurological disease characterized by inflammatory lesions in the central nervous system. Hence, predicting inflammatory disease activity is crucial for disease assessment and treatment. However, MS…

图像与视频处理 · 电气工程与系统科学 2023-09-01 Chinmay Prabhakar , Hongwei Bran Li , Johannes C. Paetzold , Timo Loehr , Chen Niu , Mark Mühlau , Daniel Rueckert , Benedikt Wiestler , Bjoern Menze

In recent years, several convolutional neural network (CNN) methods have been proposed for the automated white matter lesion segmentation of multiple sclerosis (MS) patient images, due to their superior performance compared with those of…

Brain lesion volume measured on T2 weighted MRI images is a clinically important disease marker in multiple sclerosis (MS). Manual delineation of MS lesions is a time-consuming and highly operator-dependent task, which is influenced by…

图像与视频处理 · 电气工程与系统科学 2023-11-28 Hang Zhang , Jinwei Zhang , Qihao Zhang , Jeremy Kim , Shun Zhang , Susan A. Gauthier , Pascal Spincemaille , Thanh D. Nguyen , Mert R. Sabuncu , Yi Wang

Automated segmentation of multiple sclerosis (MS) lesions from MRI scans is important to quantify disease progression. In recent years, convolutional neural networks (CNNs) have shown top performance for this task when a large amount of…

计算机视觉与模式识别 · 计算机科学 2023-03-10 Jiacheng Wang , Hao Li , Han Liu , Dewei Hu , Daiwei Lu , Keejin Yoon , Kelsey Barter , Francesca Bagnato , Ipek Oguz

Segmentation of focal (localized) brain pathologies such as brain tumors and brain lesions caused by multiple sclerosis and ischemic strokes are necessary for medical diagnosis, surgical planning and disease development as well as other…

计算机视觉与模式识别 · 计算机科学 2017-01-25 Mohammad Havaei , Nicolas Guizard , Hugo Larochelle , Pierre-Marc Jodoin

Multiple sclerosis (MS) is an inflammatory demyelinating disease of the central nervous system (CNS) that results in focal injury to the grey and white matter. The presence of white matter lesions biases morphometric analyses such as…

计算机视觉与模式识别 · 计算机科学 2019-09-09 Hao Xiong , Chaoyue Wang , Dacheng Tao , Michael Barnett , Chenyu Wang

Accurate segmentation of Multiple Sclerosis (MS) lesions in longitudinal MRI scans is crucial for monitoring disease progression and treatment efficacy. Although changes across time are taken into account when assessing images in clinical…

Segmentation of Multiple Sclerosis (MS) lesions is a challenging problem. Several deep-learning-based methods have been proposed in recent years. However, most methods tend to be static, that is, a single model trained on a large,…

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