Artificial Intelligence Algorithm-Based Lumbar and Spinal MRI for Evaluation of Efficacy of Chinkuei Shin Chewan Decoction on Lumbar Spinal Stenosis

• Published in: Contrast media and molecular imaging 2021-12, Vol.2021, p.2700452-10
• Main Authors: Zhu, Yuefeng, Wu, Tao, Wang, Wenhao, Cai, Chengchen, Zhu, Bin, Lin, Weilong, Xu, Hao, Liang, Qianqian, Wang, Yongjun
• Format: Article
• Language: English
• Subjects: Algorithms; Artificial Intelligence; Humans; Lumbar Vertebrae - diagnostic imaging; Magnetic Resonance Imaging; Spinal Stenosis - diagnostic imaging; Spinal Stenosis - drug therapy; Treatment Outcome
• ISSN: 1555-4309; 1555-4317
• DOI: 10.1155/2021/2700452

The study aimed to explore the application value of lumbar Magnetic Resonance Imaging (MRI) images processed by artificial intelligence algorithms in evaluating the efficacy of chinkuei shin chewan decoction (a traditional Chinese medicine to nourish the kidney) in the treatment of lumbar spinal stenosis (LSS). Specifically, 110 LSS patients admitted to the hospital were selected as the research subjects. They were randomly divided into the control group (n = 55) and experimental group (n = 55) according to different treatment methods. The control group was treated with traditional medicine, and the experimental group additionally took chinkuei shin chewan decoction on its basis. Based on the traditional U-net algorithm, a U-net registration algorithm based on artificial intelligence was designed by introducing the information entropy theory, and the algorithm was applied to the lumbar MRI image evaluation of LSS patients. Compared with the traditional U-net algorithm, the artificial intelligence-based U-net registration algorithm had a decreased noise level P