Toward reliable automatic liver and tumor segmentation using convolutional neural network based on 2.5D models

Abstract

This paper compares the performance of the network based on 2.5D model using different parameter configurations. The result obtained shows the effect of each parameter and allow the selection of the best configuration in order to improve the network performance in the application of automatic liver and tumor segmentation.