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Graph convolutional networks for region of interest classification in breast histopathology
2020
Medical Imaging 2020: Digital Pathology
Deep learning-based approaches have shown highly successful performance in the categorization of digitized biopsy samples. The commonly used setting in these approaches is to employ convolutional neural networks for classification of data sets consisting of images all having the same size. However, the clinical practice in breast histopathology necessitates multi-class categorization of regions of interest (ROI) in biopsy samples where these regions can have arbitrary shapes and sizes. The
doi:10.1117/12.2550636
dblp:conf/midp/AygunesACKOU20
fatcat:2trj4r7qlbctnitcdqtfcquzsi