Toward reliable automatic liver and tumor segmentation using convolutional neural network based on 2.5D models.
Journal:
International journal of computer assisted radiology and surgery
Published Date:
Nov 21, 2020
Abstract
PURPOSE: We investigated the parameter configuration in the automatic liver and tumor segmentation using a convolutional neural network based on 2.5D model. The implementation of 2.5D model shows promising results since it allows the network to have a deeper and wider network architecture while still accommodates the 3D information. However, there has been no detailed investigation of the parameter configurations on this type of network model.