Abstract #2638

Automatic detection of cognitive impairment in patients with White matter hyperintensity based on deep learning and radiomics of MRI

Junbang Feng¹, Qingqing Zheng², Yuwei Xia³, Shi Feng ³, Qing Zhou³, Hang Yin¹, Shike Wang², and Chuanming Li¹

¹Medical Imaging Department, Chongqing University Central Hospital, Chongqing, China, ²The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China, ³Shanghai United Imaging Intelligence, Co., Ltd., Shanghai, China

Synopsis

Keywords: White Matter, Machine Learning/Artificial IntelligenceWhite matter hyperintensity (WMH) is common in the aging brain, which is associated with cognitive decline and dementia. At present, there is still no objective method for early detection of cognitive impairment from these populations. In this study, deep learning and radiomics techniques were used to automatically segment and extract the characteristics of WMH and other regional brain tissues, and models were established to detect mild cognitive impairment.

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