Automatic classification of lung nodule candidates based on a novel 3D convolution network and knowledge transferred from a 2D network.
Journal:
Medical physics
Published Date:
Nov 6, 2019
Abstract
OBJECTIVE: In the automatic lung nodule detection system, the authenticity of a large number of nodule candidates needs to be judged, which is a classification task. However, the variable shapes and sizes of the lung nodules have posed a great challenge to the classification of candidates. To solve this problem, we propose a method for classifying nodule candidates through three-dimensional (3D) convolution neural network (ConvNet) model which is trained by transferring knowledge from a multiresolution two-dimensional (2D) ConvNet model.