Automatic Extraction of Appendix from Ultrasonography with Self-Organizing Map and Shape-Brightness Pattern Learning

Biomed Res Int. 2016:2016:5206268. doi: 10.1155/2016/5206268. Epub 2016 Apr 12.

Abstract

Accurate diagnosis of acute appendicitis is a difficult problem in practice especially when the patient is too young or women in pregnancy. In this paper, we propose a fully automatic appendix extractor from ultrasonography by applying a series of image processing algorithms and an unsupervised neural learning algorithm, self-organizing map. From the suggestions of clinical practitioners, we define four shape patterns of appendix and self-organizing map learns those patterns in pixel clustering phase. In the experiment designed to test the performance for those four frequently found shape patterns, our method is successful in 3 types (1 failure out of 45 cases) but leaves a question for one shape pattern (80% correct).

MeSH terms

  • Algorithms
  • Appendicitis / diagnosis*
  • Appendicitis / diagnostic imaging*
  • Appendicitis / physiopathology
  • Female
  • Humans
  • Image Processing, Computer-Assisted / methods*
  • Pregnancy
  • Ultrasonography / methods*