基于深度学习的阴道镜图像辅助诊断研究进展

Yehong Huang
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摘要

宫颈癌是女性中最常见的恶性肿瘤之一;因此,全世界一直在努力提高宫颈癌的有效筛查和预防。阴道镜检查在宫颈癌预防中起着核心作用,但其准确性和可重复性仍然有限。深度学习在医学图像领域的应用,可以让更多的研究者探索深度学习在阴道镜图像辅助诊断中的应用。本文总结了该领域的研究现状,提出了该研究领域目前存在的不足和改进方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research Progression of Colposcopy Image-assisted Diagnosis Based on Deep Learning
Cervical cancer is one of the most common malignant tumors in women; hence the world has been working to improve the effective screening and prevention of cervical cancer. Colposcopy plays a central role in cervical cancer prevention, but its accuracy and reproducibility are still limited. The use of deep learning in the field of medical images allows more researchers as well as to explore the application of deep learning in colposcopy image-assisted diagnosis. In this paper, we summarize the research status of this field and propose the current shortcomings and improvement directions this research field.
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