Medical image segmentation by more sensitive adaptive thresholding

Cheolhwan Kim, Jiyoung Yoon, Yun Jung Lee

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

7 Scopus citations

Abstract

To make 3D surface model from medical images, segmentation is essential process. And, in the case that the HU(Hounsfield Unit) values of the object to be segmented varies in the image, adaptive thresholding segmentation is very efficient segmentation method. But in many cases, it shows insufficient sensitivity of segmentation that weak(dim) objects are not segmented. This problem is caused mainly by strong(bright) object nearby the weak object because adaptive thresholding makes high threshold due to strong object. In this study we present a more sensitive adaptive thresholding method overcoming this problem.

Original languageEnglish
Title of host publication2016 6th International Conference on IT Convergence and Security, ICITCS 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509037643
DOIs
StatePublished - 9 Nov 2016
Event6th International Conference on IT Convergence and Security, ICITCS 2016 - Prague, Czech Republic
Duration: 26 Sep 201629 Sep 2016

Publication series

Name2016 6th International Conference on IT Convergence and Security, ICITCS 2016

Conference

Conference6th International Conference on IT Convergence and Security, ICITCS 2016
Country/TerritoryCzech Republic
CityPrague
Period26/09/1629/09/16

Keywords

  • Adaptive
  • Image
  • Medical
  • Segmentation
  • Sensitive
  • Thresholding

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