Preliminary Clinical Study of the Differences Between Interobserver Evaluation and Deep Convolutional Neural Network-Based Segmentation of Multiple Organs at Risk in CT Images of Lung Cancer.

ABSTRACT: Background: In this study, publicly datasets with organs at risk (OAR) structures were used as reference data to compare the differences of several observers. Convolutional neural network (CNN)-based auto-contouring was also used in the analysis. We evaluated the variations among observers and the effect of CNN-based auto-contouring in clinical applications. Materials and methods: A total of 60 publicly available lung cancer CT with structures were used; 48 cases were used for training, and the other 12 cases were used for testing. The structures of the datasets were used as reference data. Three observers and a CNN-based program performed contouring for 12 testing cases, and the 3D dice similarity coefficient (DSC) and mean surface distance (MSD) were used to evaluate differ

SUBMITTER: Zhu J 

PROVIDER: S-EPMC6624788 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature