Lung cancer risk estimation on thorax CT scans - DSB2017 JulianDaniel


Logo for Lung cancer risk estimation on thorax CT scans - DSB2017 JulianDaniel

About

Version:
2cad5396-4633-4006-9620-5761b7ab66d7
Last updated:
Sept. 30, 2020, 5:41 p.m.
Associated publication:
Jacobs C, Setio AAA, Scholten ET, et al.. Deep Learning for Lung Cancer Detection on Screening CT Scans: Results of a Large-Scale Public Competition and an Observer Study with 11 Radiologists. Radiology: Artificial Intelligence. 2021;3(6).
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.)

Summary

This algorithm analyzes non-contrast CT scans of the thorax and predicts the lung cancer risk. The algorithm was developed by Julian de Wit and Daniel Hammack. The algorithm descriptions and code are publicly available: report Daniel Hammack, code Daniel Hammack, report Julian de Wit, code Julian de Wit.

This algorithm was developed as part of the Kaggle Data Science Bowl in 2017 and won the second place in this challenge.

Uses and Directions

This algorithm was developed for research purposes only.