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Modeling of Clinical Mammography Recognition

机译:临床乳腺X线摄影识别模型

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摘要

Breast cancer screening can detect and treat early, mammography is one of popular screening methods. Recognition of mammography image depends on the radiologist, but human interpretation of mammography image has its limitations. Recently, for precision medicine, deep learning technology is applied on medical images to reduce the risk of the interpretation on breast lesion types (BIRADS, Breast Imaging Reporting and Data System, divided into 0 to 6 categories). This study proposes a mammography recognition model that is based on deep learning method to support clinical diagnosis of breast cancer. The model is try to improve medical quality.
机译:乳腺癌筛查可以及早发现并治疗,乳房X线照相术是流行的筛查方法之一。乳腺X射线摄影图像的识别取决于放射科医生,但是人类对乳腺X射线摄影图像的解释有其局限性。最近,对于精密医学,深度学习技术已应用于医学图像,以降低对乳腺病变类型进行解释的风险(BIRADS,乳腺成像报告和数据系统,分为0至6类)。这项研究提出了一种基于深度学习方法的乳房X线照片识别模型,以支持乳腺癌的临床诊断。该模型是试图提高医疗质量。

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