CXR Cardiomegaly Detection

About

Creators:

ecemsogancioglu

BramVanGinneken

Contact email:

ecem.sogancioglu@radboudumc.nl

Version:

dc28629c-fef1-4ee8-939a-5b80dce20804

Last updated:

May 7, 2020, 12:45 p.m.

Associated publication:

Sogancioglu E, Murphy K, Calli E, Scholten ET, Schalekamp S, Van Ginneken B. Cardiomegaly Detection on Chest Radiographs: Segmentation Versus Classification. IEEE Access. 2020;8:94631-94642.

Inputs:

Generic Medical Image

Outputs:

Generic Overlay (An overlay of unknown type. Legacy, please use alternative interfaces.)
Results JSON File (A collection of results of unknown type. Legacy, if possible please use alternative interfaces.)

Model Facts

Summary

The algorithm detects cardiomegaly and computes the cardiothoracic ratio on chest radiographs through the segmentation of the heart and lungs.

Mechanism

Input¶

The input should be a frontal chest radiograph. The following file formats are supported: .mha, .mhd, .png, .dcm, .jpeg. The algorithm has been trained with posterior-anterior images (regular frontal chest x-rays, not bed-side images).

Publication¶

This algorithm is described in IEEE Access.

Contact Information¶

Questions related to this algorithm can be addressed to Ecem Sogancioglu.

Validation and Performance

Left empty by the Algorithm Editors

Uses and Directions

This algorithm was developed for research purposes only.

Warnings

Left empty by the Algorithm Editors

Common Error Messages

Left empty by the Algorithm Editors

Information on this algorithm has been provided by the Algorithm Editors, following the Model Facts labels guidelines from Sendak, M.P., Gao, M., Brajer, N. et al. Presenting machine learning model information to clinical end users with model facts labels. npj Digit. Med. 3, 41 (2020). 10.1038/s41746-020-0253-3