Automatic Feature Learning Using Multichannel ROI Based on Deep Structured Algorithms for Computerized Lung Cancer Diagnosis

This study aimed to analyze the ability of extracting automatically generated features using deep structured algorithms in lung nodule CT image diagnosis, and compare its performance with traditional computer aided diagnosis (CADx) systems using hand-crafted features. All of the 1018 cases were acquired from Lung Image Database Consortium (LIDC) public lung cancer database. The nodules were segmented according to four radiologists ’ markings, and 134668 samples were generated by rotating every slice of nodule images.

Source: Computers in Biology and Medicine - April 13, 2017 Category: Bioinformatics Authors: Wenqing Sun, Bin Zheng, Wei Qian Source Type: research