Fully Automatic Volume Measurement of the Spleen at CT Using Deep Learning.

ABSTRACT:

Purpose

To develop a fully automated algorithm for spleen segmentation and to assess the performance of this algorithm in a large dataset.

Materials and methods

In this retrospective study, a three-dimensional deep learning network was developed to segment the spleen on thorax-abdomen CT scans. Scans were extracted from patients undergoing oncologic treatment from 2014 to 2017. A total of 1100 scans from 1100 patients were used in this study, and 400 were selected for development of the algorithm. For testing, a dataset of 50 scans was annotated to assess the segmentation accuracy and was compared against the splenic index equation. In a qualitative observer experiment, an enriched set of 100 scan-pairs was used to evaluate whether the algorithm could aid a radiologist in as

SUBMITTER: Humpire-Mamani GE 

PROVIDER: S-EPMC8082410 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature