[1]FU Changyang,WANG Yu,XIAO Hongbing,et al.Assisted diagnosis of major depression disorder using deep learning and structural magnetic resonance imaging[J].CAAI Transactions on Intelligent Systems,2021,16(3):544-551.[doi:10.11992/tis.201912006]
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CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume:
16
Number of periods:
2021 3
Page number:
544-551
Column:
学术论文—人工智能基础
Public date:
2021-05-05
- Title:
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Assisted diagnosis of major depression disorder using deep learning and structural magnetic resonance imaging
- Author(s):
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FU Changyang; WANG Yu; XIAO Hongbing; XING Suxia
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Beijing Key Lab of Food Safety Big Data Technology, Beijing Technology and Business University, Beijing 100048, China
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- Keywords:
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depression; diagnosis; computer vision; deep learning; optimization; transfer learning; structural magnetic resonance image; classification
- CLC:
-
TP181
- DOI:
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10.11992/tis.201912006
- Abstract:
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Depression is one of the diseases with the highest disability and morbidity. About 300 million people around the world are suffering from depression. However, there exist no effective biological characteristics and clinical methods to help doctors diagnose depression accurately. In this study, the state-of-the-art deep learning model in the field of computer vision is optimized and adapted to diagnose depression. On this basis, transfer learning is introduced, achieving excellent results. Experimental results reveal that compared with the frontier algorithm model, the proposed method can effectively improve the classification accuracy and recall of the structural magnetic resonance image of control subjects who are healthy and those who are depressed, which fully verifies the effectiveness and superiority of the proposed method.