人工智能
计算机科学
预处理器
疾病
脑病
神经影像学
机器学习
数据科学
模式识别(心理学)
医学
病理
心理学
神经科学
作者
Chenxi Huang,Jian Wang,Shuihua Wang,Yudong Zhang
标识
DOI:10.1016/j.neucom.2022.07.005
摘要
Brain diseases threaten hundreds of thousands of people over the world. Medical imaging techniques such as MRI and CT are employed for various brain disease studies. As artificial intelligence succeeded in image analysis, scientists employed artificial intelligence, especially deep learning technologies, to assist brain disease studies. The AI applications for brain disease studies can be divided into two categories. The first category is preprocessing, including denoising, registration, skull-stripping, intensity normalization, and data augmentation. The second category is the clinical application that contains lesion segmentation, disease detection, grade classification, and outcome prediction. In this survey, we reviewed over one hundred representative papers on how to apply AI to brain disease studies. We first introduced AI-based preprocessing for brain disease studies. Second, we reviewed the influential works of AI-based brain disease studies. At last, we also discussed three development trends in the future. We hope this survey will inspire both expert-level researchers and entry-level beginners.
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