基于脑MRI的自身免疫性疾病深度学习诊断

D. Amanatidis, Georgios Chatzisavvas, Michael F. Dossis
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引用次数: 0

摘要

自身免疫性疾病的诊断通常需要仔细检查患者的健康史,并评估任何可能的职业和环境相关暴露。通常,自身免疫性疾病有早期症状,如关节和肌肉疼痛、疲劳、体重减轻或发烧。然而,这些症状是非特异性的,成像技术工具对于精确诊断是非常有价值的。在本文中,我们处理自身免疫性疾病,导致脑损伤,更具体地说,多发性硬化症。利用卷积神经网络对脑MRI图像进行分类,结果非常好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Brain MRI based diagnosis of autoimmune diseases using deep learning
The diagnosis of an autoimmune disease usually requires a careful examination of the patient’s health history and the evaluation of any possible occupation and environment related exposures. Frequently, autoimmune disorders have early symptoms such as joint and muscle pain, fatigue, weight loss or fever. These symptoms however are non-specific and imaging technology tools can be extremely valuable for precise diagnosis. In this paper, we deal with autoimmune diseases that result in brain damage and more specifically, multiple sclerosis. Classification of brain MRI images is performed leveraging a Convolutional Neural Network, showing excellent results.
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期刊介绍: Computer Engineering and Design is supervised by China Aerospace Science and Industry Corporation and sponsored by the 706th Institute of the Second Academy of China Aerospace Science and Industry Corporation. It was founded in 1980. The purpose of the journal is to disseminate new technologies and promote academic exchanges. Since its inception, it has adhered to the principle of combining depth and breadth, theory and application, and focused on reporting cutting-edge and hot computer technologies. The journal accepts academic papers with innovative and independent academic insights, including papers on fund projects, award-winning research papers, outstanding papers at academic conferences, doctoral and master's theses, etc.
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