Snake-Aided Automatic Organ Delineation

Weibing Xu, Saad A. Amin, Olivier C.L. Haas, Keith J. Burnham, John A. Mills

Research output: Chapter in Book/Report/Conference proceedingConference proceedingpeer-review


This paper presents a knowledge-based image segmentation tool for organ delineation in CT (Computed Tomography) images. The noise and low contrast make the detection difficult. Therefore in this method, radial search, noise reduction method and post-processing algorithm have been implemented to improve the quality of contour detection. Three edge detection algorithms have been used and after detection several optimization methods have been employed to get the accurate contour from three detected contours. Finally to achieve higher accuracy of detection, active contour model (ACM), snake, has been used after the contour detected by previous methods.
Original languageEnglish
Title of host publicationPattern Recognition: 26th DAGM Symposium, Tübingen, Germany, August 30 - September 1, 2004. Proceedings
EditorsCarl Edward Rasmussen, Heinrich H. Bülthoff, Bernhard Schölkopf, Martin A. Giese
PublisherSpringer Verlag
Number of pages8
VolumeLecture Notes in Computer Science 3175
ISBN (Print)978-3-540-22945-2
Publication statusPublished - 2004
EventDAGM Symposium 2004 - Tubingen, Germany
Duration: 30 Aug 20041 Sept 2004


ConferenceDAGM Symposium 2004

Bibliographical note

This article is not yet available on the repository. The paper was given at the 26th DAGM Symposium, Tübingen, Germany, August 30 - September 1, 2004.


  • Pattern Recognition
  • Image Processing and Computer Vision
  • Artificial Intelligence (incl. Robotics)
  • Computer Graphics
  • Algorithm Analysis and Problem Complexity


Dive into the research topics of 'Snake-Aided Automatic Organ Delineation'. Together they form a unique fingerprint.

Cite this