机译:利用计算机辅助诊断选择乳房MRI时空特征以区分恶性和良性小病变
Department of Computer Science, Technical University of Munich, 8574 Garching, Germany;
Department of Scientific Computing, Florida State University, Tallahassee, FL 32306-4120, USA;
Department of Scientific Computing, Florida State University, Tallahassee, FL 32306-4120, USA;
Institute for Clinical Radiology, University of Munich, 81377 Munich, Germany;
Department of Electrical and Computer Engineering, FAMU/FSU College of Engineering, Tallahassee, FL 32310-6046, USA;
机译:利用计算机辅助诊断选择乳房MRI时空特征以区分恶性和良性小病变
机译:使用计算机辅助诊断选择乳房MRI的诊断特征,以区分恶性和良性病变:病变表现为肿块和非肿块样增强。
机译:使用计算机辅助诊断选择乳腺MRI的诊断特征以区分恶性和良性病变:病变表现为肿块和非肿块样增强的差异
机译:使用基于Curvelet的纹理特征区分乳腺DCE-MRI良性和恶性非肿块
机译:区分乳腺良性和恶性炎症病变:T2加权和弥散加权MR图像的价值
机译:使用计算机辅助诊断选择乳腺MRI的诊断特征以区分恶性和良性病变:病变表现为肿块和非肿块样增强的差异
机译:使用计算机辅助诊断选择乳腺MRI的诊断特征以区分恶性和良性病变:病变表现为肿块和非肿块样增强的差异