基于深度神经网络的骨科图像分割与识别

Kaiyang Zhang
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引用次数: 0

摘要

在医学领域,尤其是骨科领域,准确的诊断至关重要。然而,由于医疗资源分配不均和患者人数的持续增长,医院的诊断效率受到很大影响,误诊和漏诊问题日益突出。针对这些问题,本研究探索了一种基于深度神经网络的骨科图像分割与识别模型,旨在提高诊断的准确性和效率。首先,我们使用 U-Net 神经网络对骨科图像进行分割训练,以提取图像中的细节特征。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Orthopedic Image Segmentation and Recognition Based on Deep Neural Networks
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.
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