Automated 3-D segmentation of internal hemoglobin in TEM images

Sunil Seepuri, Jeffrey J. Rodríguez, David A. Elliott

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Active contour models or snakes are widely used for medical image segmentation, due to their robustness to images with weak borders and poor contrast, and their ability to provide smooth contours. However, initialization is a serious problem for active contours and they tend to be attracted towards inappropriate image features if the initialization is not proper. In this paper, we propose a method that combines region growing and active contours for segmenting internal hemoglobin in transmission electron micrograph images of malaria parasites. Region growing is used in each image slice to provide the initial contour for the snake, which then determines the final contour based on the gradient vector field. Experimental results demonstrate the effectiveness of the proposed scheme in terms of segmentation quality and accuracy.

Original languageEnglish (US)
Title of host publication2008 IEEE Southwest Symposium on Image Analysis and Interpretation, SSIAI 2008 - Proceedings
Pages117-120
Number of pages4
DOIs
StatePublished - Dec 1 2008
Event2008 IEEE Southwest Symposium on Image Analysis and Interpretation, SSIAI 2008 - Santa Fe, NM, United States
Duration: Mar 24 2008Mar 26 2008

Publication series

NameProceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation

Other

Other2008 IEEE Southwest Symposium on Image Analysis and Interpretation, SSIAI 2008
CountryUnited States
CitySanta Fe, NM
Period3/24/083/26/08

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

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    Seepuri, S., Rodríguez, J. J., & Elliott, D. A. (2008). Automated 3-D segmentation of internal hemoglobin in TEM images. In 2008 IEEE Southwest Symposium on Image Analysis and Interpretation, SSIAI 2008 - Proceedings (pp. 117-120). [4512299] (Proceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation). https://doi.org/10.1109/SSIAI.2008.4512299