Automatic detection of structural changes in single channel long time-span brain MRI images using saliency map and active contour methods

Andrea Kovacs, Tamas Sziranyi, Peter Barsi

Research output: Conference contribution

Abstract

This paper introduces a novel method to detect structural changes between MRI scans, without using prior knowledge. After a simple registration step, the method calculates a difference image, based on modified Harris saliency function, which is then used to define change candidates. Localization step filters out false hits with local contour descriptors featuring the neighborhood of candidates. Finally, boundary of the lesion is detected by integration of contour point extraction and Chan-Vese active contour method. Tests on simulated and real data show that the results are very promising.

Original languageEnglish
Title of host publication2012 IEEE International Conference on Image Processing, ICIP 2012 - Proceedings
Pages1265-1268
Number of pages4
DOIs
Publication statusPublished - dec. 1 2012
Event2012 19th IEEE International Conference on Image Processing, ICIP 2012 - Lake Buena Vista, FL, United States
Duration: szept. 30 2012okt. 3 2012

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880

Other

Other2012 19th IEEE International Conference on Image Processing, ICIP 2012
CountryUnited States
CityLake Buena Vista, FL
Period9/30/1210/3/12

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems

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    Kovacs, A., Sziranyi, T., & Barsi, P. (2012). Automatic detection of structural changes in single channel long time-span brain MRI images using saliency map and active contour methods. In 2012 IEEE International Conference on Image Processing, ICIP 2012 - Proceedings (pp. 1265-1268). [6467097] (Proceedings - International Conference on Image Processing, ICIP). https://doi.org/10.1109/ICIP.2012.6467097