Computer-Aided Detection and Diagnosis of Breast Cancer With Mammography: Recent Advances

By Jinshan Tang, Rangaraj Mandayam Rangayyan, Jun Xu, Issam El-Naqa, Yongyi Yang. IEEE Transactions on Information Technology in Biomedicine, 2009

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Machine Learning and Radiology (2012, positive): “SVMs perform well in detection of microcalcifications on mammography CAD (El-Naqa et al., 2002; Tang et al., 2009; Wei et al., 2005b).”
The impact of pre- and post-image processing techniques on deep learning frameworks: A comprehensive review for digital pathology image analysis (2020, methodology): “This motivated the development of automated systems to increase the level of inter-observer agreement and improve diagnosis efficiency [113].”
Breast cancer detection using deep convolutional neural networks and support vector machines (2019, background): “In addition, the malignant mass will appear whiter than any tissue surrounding it ( Tang et al., 2009 ).”
Histopathological Image Analysis: A Review (2009, background): “become a part of routine clinical detection of breast cancer on mammograms at many screening sites and hospitals [2] in”