3D G-CNNs for Pulmonary Nodule Detection

12 Apr 2018 Marysia Winkels Taco S. Cohen

Convolutional Neural Networks (CNNs) require a large amount of annotated data to learn from, which is often difficult to obtain in the medical domain. In this paper we show that the sample complexity of CNNs can be significantly improved by using 3D roto-translation group convolutions (G-Convs) instead of the more conventional translational convolutions... (read more)

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