Spleen Segmentation


Logo for Spleen Segmentation

About

Image Version:
e9694929-e0fd-42af-8fba-318282d55f02
Last updated:
April 4, 2019, 4:42 p.m.

Interfaces

This algorithm implements all of the following input-output combinations:

Inputs Outputs
1
  • Generic Medical Image (Image)
  • Generic Overlay (Heat Map)
  • Results JSON File (Anything)
  • Model Facts

    Summary

    General information

    This algorithm fully automatically performs a volumetric segmentation of the spleen on contrast-enhanced thorax-abdomen CT scans. The underlying algorithm is a 3D U-Net model trained and validated on a large set of contrast-enhanced CT thorax abdomen scans from one academic center in the Netherlands. A large proportion of the training scans came from oncological follow-up and hence contained a wide variety of abnormalities and pathology. The algorithm and its validation is described in this publication in Radiology: Artificial Intelligence .

    Contact information

    For questions about this algorithm, please contact Colin Jacobs.

    Mechanism

    Validation and Performance

    Uses and Directions

    This algorithm was developed for research purposes only.

    Warnings

    Common Error Messages

    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