Adaptive active-mask image segmentation for quantitative characterization of mitochondrial morphology

Kuan Chieh Jackie Chen, Yiyi Yu, Ruiqin Li, Hao Chih Lee, Ge Yang, Jelena Kovacevic

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

Abstract

We propose an automated algorithm for segmentation of mitochondria from widefield fluorescence microscopy images for quantitative morphology characterization. Mitochondria are membrane-bound organelles that are essential to cells of higher living organisms. Reliable and precise quantitative characterization of their shape is crucial to understanding related physiology and disease mechanisms. Building upon the active-mask framework developed for segmentation of confocal fluorescence microscope images, we propose a new adaptive region-based distributing function to effectively address the problem of halo artifacts that are common in widefield fluorescence images. Such artifacts prevent the segmentation of weak features of mitochondria using existing algorithms. We compare the algorithm to the original active-mask algorithm as well as the geodesic active contour algorithm based on hand-segmented ground truth, and find that it performs significantly better both qualitatively and quantitatively.

Original languageEnglish (US)
Title of host publication2012 IEEE International Conference on Image Processing, ICIP 2012 - Proceedings
Pages2033-2036
Number of pages4
DOIs
StatePublished - Dec 1 2012
Event2012 19th IEEE International Conference on Image Processing, ICIP 2012 - Lake Buena Vista, FL, United States
Duration: Sep 30 2012Oct 3 2012

Other

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

Fingerprint

Image segmentation
Masks
Mitochondria
Fluorescence
Fluorescence microscopy
Physiology
Microscopes
Membranes

Keywords

  • active masks
  • mitochondria
  • segmentation

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems

Cite this

Chen, K. C. J., Yu, Y., Li, R., Lee, H. C., Yang, G., & Kovacevic, J. (2012). Adaptive active-mask image segmentation for quantitative characterization of mitochondrial morphology. In 2012 IEEE International Conference on Image Processing, ICIP 2012 - Proceedings (pp. 2033-2036). [6467289] https://doi.org/10.1109/ICIP.2012.6467289

Adaptive active-mask image segmentation for quantitative characterization of mitochondrial morphology. / Chen, Kuan Chieh Jackie; Yu, Yiyi; Li, Ruiqin; Lee, Hao Chih; Yang, Ge; Kovacevic, Jelena.

2012 IEEE International Conference on Image Processing, ICIP 2012 - Proceedings. 2012. p. 2033-2036 6467289.

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

Chen, KCJ, Yu, Y, Li, R, Lee, HC, Yang, G & Kovacevic, J 2012, Adaptive active-mask image segmentation for quantitative characterization of mitochondrial morphology. in 2012 IEEE International Conference on Image Processing, ICIP 2012 - Proceedings., 6467289, pp. 2033-2036, 2012 19th IEEE International Conference on Image Processing, ICIP 2012, Lake Buena Vista, FL, United States, 9/30/12. https://doi.org/10.1109/ICIP.2012.6467289
Chen KCJ, Yu Y, Li R, Lee HC, Yang G, Kovacevic J. Adaptive active-mask image segmentation for quantitative characterization of mitochondrial morphology. In 2012 IEEE International Conference on Image Processing, ICIP 2012 - Proceedings. 2012. p. 2033-2036. 6467289 https://doi.org/10.1109/ICIP.2012.6467289
Chen, Kuan Chieh Jackie ; Yu, Yiyi ; Li, Ruiqin ; Lee, Hao Chih ; Yang, Ge ; Kovacevic, Jelena. / Adaptive active-mask image segmentation for quantitative characterization of mitochondrial morphology. 2012 IEEE International Conference on Image Processing, ICIP 2012 - Proceedings. 2012. pp. 2033-2036
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