Automatic segmentation of bone tissue in x-ray hand images

Ayhan Yuksel*, Tamer Olmez

*Corresponding author for this work

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

2 Citations (Scopus)

Abstract

Automatic segmentation of X-ray hand images is an important process. In studies such as skeletal bone age assessment, bone densitometry and analyzing of bone fractures, it is a necessary extremely difficult and complicated task. In this study, hand X-ray images were segmented by using C-means classifier. Extraction of bone tissue was realized in three steps: i) preprocessing, ii) feature extraction and iii) automatic segmentation. In preprocessing scheme, inhomogeneous intensity distribution is eliminated and some structural pre-information about hand was obtained in order to use in feature extraction block. In feature extraction process, edges between soft and bone tissues were extracted by proposed enhancement process. In automatic segmentation process, the image was segmented using C-mean classifier by taking care of local information. In the study, hand images of ten different people were segmented with high performances above 95%.

Original languageEnglish
Title of host publicationAdaptive and Natural Computing Algorithms - 9th International Conference, ICANNGA 2009, Revised Selected Papers
Pages590-599
Number of pages10
DOIs
Publication statusPublished - 2009
Event9th International Conference on Adaptive and Natural Computing Algorithms, ICANNGA 2009 - Kuopio, Finland
Duration: 23 Apr 200925 Apr 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5495 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference9th International Conference on Adaptive and Natural Computing Algorithms, ICANNGA 2009
Country/TerritoryFinland
CityKuopio
Period23/04/0925/04/09

Keywords

  • Classifiers
  • Hand radiographs
  • Image segmentation

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