用于肺结节检测的三维G-CNNs

Apr, 2018

3D G-CNNs for Pulmonary Nodule Detection

Marysia Winkels, Taco S. Cohen

TL;DR使用3D roto-translation group convolutions （G-Convs）能够有效地降低Convolutional Neural Networks的样本复杂度，从而更好实现肺结节检测中假阳性的过滤，从而达到了比基线体系结构更高的敏感性和收敛速度。

Abstract

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