Orthopedic Image Segmentation and Recognition Based on Deep Neural Networks
Journal: Journal of Clinical Medicine Research DOI: 10.32629/jcmr.v5i2.2332
Abstract
In the field of medicine, especially orthopedics, accurate diagnosis is crucial. However, due to the uneven distribution of medical resources and the continuous growth of patient numbers, the diagnostic efficiency of hospitals has been significantly affected, and the problems of misdiagnosis and missed diagnosis are becoming increasingly prominent. To address these issues, this study explores a deep neural network-based orthopedic image segmentation and recognition model, aiming to improve the accuracy and efficiency of diagnosis. Firstly, we use U-Net neural network for segmentation training of orthopedic images in order to extract detailed features from the images.
Keywords
deep neural network, U-Net, ResNet50, transfer learning
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[2] Liu Yu, Chen Sheng A review of medical image segmentation methods [J] Electronic Technology, 2017, 30 (08): 169-172.
[3] Peng Jing, Luo Haoyu, Zhao Gansen, etc A review of medical image segmentation algorithms under deep learning [J] Computer Engineering and Applications, 2021, 57 (03): 44-57.
[4] Wang Lili, Wang Ying, Hao Xiaoqian Observation on the effect of optimizing emergency nursing process to shorten the treatment time of acute ischemic stroke patients [J] Chinese Geriatric Health Medicine, 2024, 22 (01): 146-149.
[5] Song Yao, Liu Jun Improved U-Net image segmentation method for COVID-19 [J] Computer Engineering and Applications, 2021, 57 (19): 243-251.
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