Imaging Science and Biomedical Engineeering, University of Manchester, Oxford Road, Manchester, Ml3 9PT, UK;
Imaging Science and Biomedical Engineeering, University of Manchester, Oxford Road, Manchester, Ml3 9PT, UK;
Department of Clinical Radiology, University of Manchester, Manchester, UK;
University of Manchester Medical School, Stopford Building, Oxford Road, Manchester M13 9PT, UK;
Nightingale Breast Centre and Genesis Prevention Centre, University Hospital of South Manchester, Southmoor Road, Manchester M23 9LT, UK;
Imaging Science and Biomedical Engineeering, University of Manchester, Oxford Road, Manchester, Ml3 9PT, UK;
mammography; breast cancer; breast mass; lesion synthesis; statistical models; DT-CWT;
机译:在数字乳房X线照片中从正常组织中区分恶性肿块的一种自动方法。
机译:三种机器学习方法,使用数字乳房X线图的纹理特征预测良性或恶性乳房肿块
机译:放射科医师通过计算机辅助诊断在系列乳房X线照片上对恶性和良性乳腺肿块的表征得到改善:ROC研究。
机译:在正常乳房X光线照片中综合恶性乳腺菌肿块
机译:正常和恶性乳腺组织微血管中流体和溶质运移的多物理场模型,用于乳腺癌的检测和治疗。
机译:乳腺肿块的计算机辅助检测系统:全场数字乳房X线照片和数字化屏幕胶片X线照片的性能比较
机译:用于乳房群体的计算机辅助检测系统:全场数字乳房X光检查和数字化屏幕乳房X线图的性能比较
机译:解剖RhoC GTpase在正常和恶性乳腺癌中的分子机制。