模态(人机交互)
计算机辅助设计
乳腺癌
医学
超声科
乳房成像
混淆
放射科
乳腺超声检查
计算机科学
计算机辅助诊断
超声波
乳腺摄影术
医学物理学
人工智能
癌症
病理
内科学
工程制图
工程类
作者
Ali Abbasian Ardakani,Afshin Mohammadi,Mohammad Mirza‐Aghazadeh‐Attari,U. Rajendra Acharya
标识
DOI:10.1016/j.compbiomed.2022.106438
摘要
Breast cancer is one of the largest single contributors to the burden of disease worldwide. Early detection of breast cancer has been shown to be associated with better overall clinical outcomes. Ultrasonography is a vital imaging modality in managing breast lesions. In addition, the development of computer-aided diagnosis (CAD) systems has further enhanced the importance of this imaging modality. Proper development of robust and reproducible CAD systems depends on the inclusion of different data from different populations and centers to considerate all variations in breast cancer pathology and minimize confounding factors. The current database contains ultrasound images and radiologist-defined masks of two sets of histologically proven benign and malignant lesions. Using this and similar pieces of data can aid in the development of robust CAD systems.
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