Assistant Diagnosis of Insanity Based on Infrared Thermal Image Analysis and Deep Learning Algorithm. Issue 1 (February 2021)

• Record Type: Journal Article
• Authors: Wang, Yeping; Wang, Xi; Xiao, Peng; Chen, Cheng; Xiao, Ruoxiu; Wang, Yanshen; Lu, Yuanyuan; Wang, Zhiliang
• Is Part Of: Journal of physics. Volume 1813:Issue 1(2021)
• Publication Date: 2021-02
• Subjects: Insanity -- Infrared thermography -- Image segmentation -- Deep learning.; Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1813/1/012050
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: Considering the lack of in-depth research on the cases of insanity and other mental diseases in the context of traditional Chinese medicine, an deep learning based algorithm which can realize auxiliary judgment function of insanity are proposed in this paper. First, the original image set is screened and then an improved U-net network is used to realize the division of the trunk and limbs of the human body, thus preventing interference from disease-independent areas to affect subsequent disease judgment. Finally, based on the classification of insanity, the reference function of visual analysis is added. 1508 IR images are divided into two groups to test the proposed method. And experimental results show that accuracy of the classification of insanity diseases can reach 0.92, which has a high reference value for the clinical diagnosis of insanity.