静息状态功能磁共振成像
功能磁共振成像
功能连接
癫痫
计算机科学
神经科学
磁共振成像
人工智能
机器学习
心理学
医学
放射科
作者
Deepa Nath,Anil Hiwale,Nilesh Kurwale
出处
期刊:2021 2nd International Conference for Emerging Technology (INCET)
日期:2021-05-21
卷期号:: 1-5
被引量:1
标识
DOI:10.1109/incet51464.2021.9456231
摘要
Resting-state fMRI (rsfMRI) was firstly characterized by Biswal et al [1] in the year 1995 and since then it is used for studying patients with various neurosurgical, neurologic, and other brain-related disorders. Various statistical methods are used to analyze the resting-state functional magnetic resonance imaging connectivity. This paper attempts to explore more on the learning of resting-state functional magnetic resonance imaging connectivity. This study will help to understand the usage of rsfMRI to evaluate functional connectivity in the human brain and its usage for surgical decision-making for drug-resistant epilepsy. This paper explains the significance of such connectivity analysis, the methods available for it, and the shortcomings associated with the data.
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