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Abstract #0263

Triaging dense breast screening MR images using a dilated convolutional neural network

Angelo Zuffianò1, Bob de Vos1, Jorrit Glastra1, Pim Moeskops1, Valerio Fortunati1, Ivana Išgum2, Tim Leiner3, Carla van Gils3, and Wouter Veldhuis3
1Quantib, Utrecht, Netherlands, 2Biomedical Engineering and Physics, Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam, Netherlands, 3Radiology, Utrecht University Medical Center, Utrecht, Netherlands

Dynamic contrast enhanced (DCE) MRI is the key series to analyze for the detection of breast cancer in women with extremely dense breasts. Given the increasing number of women receiving dense breast MRI screening we aimed to reduce radiologist workload without reducing the high sensitivity of MRI. We developed a convolutional neural network (CNN) based method able to defer 8.1% of the workload by identifying non-enhancing scans with a sensitivity of 96.3%.

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