人工智能在乳腺癌超声诊断中的应用进展

Jerry Yao, Yuan Zou, Shuqian Du, Hong Wu, Bin Yuan
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摘要

乳腺是人类分泌乳汁、哺育后代的重要器官,而乳腺肿瘤则是发生在乳腺组织中的良性或恶性肿瘤。乳腺癌的病因很多,发病率持续上升,是威胁妇女健康的重要杀手。近年来,大量研究人员开始关注乳腺癌的人工智能诊断研究。人工智能利用特定算法对超声图像进行智能处理,通过对算法的训练和优化,形成高精度、高效率的乳腺癌识别模型。目前,计算机辅助检测方法在乳腺癌超声诊断中的应用已逐步推广,人工智能的结合应用在乳腺疾病超声诊断领域发挥了优势作用,如缩短检查时间、有效提高检出率和诊断准确率等。但目前乳腺疾病超声诊断技术在临床上的应用还存在一定的局限性,主要表现在:传统的基于机器学习的乳腺癌人工智能诊断模型准确率不高;本文旨在以清晰的医学图像为基础,结合计算机辅助诊断技术,有效提高乳腺疾病早期诊断的准确率,降低因医生过度劳累而导致的误诊率。
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Progress in the Application of Artificial Intelligence in Ultrasound Diagnosis of Breast Cancer
The mammary gland is an important human organ that secretes milk and feeds offspring, while breast tumors are benign or malignant tumors that occur in the breast tissue. There are many causes of breast cancer, and the incidence continues to rise, which is an important killer that threatens women's health. In recent years, a large number of researchers have been interested in the study of AI diagnosis of breast cancer. Artificial intelligence uses a specific algorithm to intelligently process ultrasound images, and develops a high-precision and high-efficiency breast cancer recognition model through training and optimization of the algorithm. At present, the application of computer-aided detection methods in breast cancer ultrasound has been gradually promoted, and the combined application of artificial intelligence has played an advantageous role in the field of breast disease ultrasound diagnosis, such as shortening the examination time, effectively improving the detection rate and diagnostic accuracy rate. The main reasons are: the accuracy of traditional AI diagnosis model of breast cancer based on machine learning is not high; The aim of this paper is to improve the accuracy of early diagnosis of breast diseases effectively and reduce the misdiagnosis rate caused by overwork of doctors on the basis of clear medical images and computer-aided diagnosis technology.
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