Segmentation of fluorescence microscopy images using three dimensional active contours with inhomogeneity correction

Soonam Lee, Paul Salama, Kenneth Dunn, Edward J. Delp

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

7 Citations (Scopus)

Abstract

Image segmentation is an important step in the quantitative analysis of fluorescence microscopy data. Since fluorescence microscopy volumes suffer from intensity inhomogeneity, low image contrast and limited depth resolution, poor edge details, and irregular structure shape, segmentation still remains a challenging problem. This paper describes a nuclei segmentation method for fluorescence microscopy based on the use of three dimensional (3D) active contours with inhomogeneity correction. The correction information utilizes 3D volume information while addressing intensity inhomogeneity across vertical and horizontal directions. Experimental results demonstrate that the proposed method achieves better performance than other reported methods.

Original languageEnglish (US)
Title of host publication2017 IEEE 14th International Symposium on Biomedical Imaging, ISBI 2017
PublisherIEEE Computer Society
Pages709-713
Number of pages5
ISBN (Electronic)9781509011711
DOIs
StatePublished - Jun 15 2017
Event14th IEEE International Symposium on Biomedical Imaging, ISBI 2017 - Melbourne, Australia
Duration: Apr 18 2017Apr 21 2017

Other

Other14th IEEE International Symposium on Biomedical Imaging, ISBI 2017
CountryAustralia
CityMelbourne
Period4/18/174/21/17

Fingerprint

Three-Dimensional Imaging
Fluorescence microscopy
Fluorescence Microscopy
Image segmentation
Chemical analysis

Keywords

  • Fluorescence microscopy
  • Image segmentation
  • Multiphoton microscopy

ASJC Scopus subject areas

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

Cite this

Lee, S., Salama, P., Dunn, K., & Delp, E. J. (2017). Segmentation of fluorescence microscopy images using three dimensional active contours with inhomogeneity correction. In 2017 IEEE 14th International Symposium on Biomedical Imaging, ISBI 2017 (pp. 709-713). [7950618] IEEE Computer Society. https://doi.org/10.1109/ISBI.2017.7950618

Segmentation of fluorescence microscopy images using three dimensional active contours with inhomogeneity correction. / Lee, Soonam; Salama, Paul; Dunn, Kenneth; Delp, Edward J.

2017 IEEE 14th International Symposium on Biomedical Imaging, ISBI 2017. IEEE Computer Society, 2017. p. 709-713 7950618.

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

Lee, S, Salama, P, Dunn, K & Delp, EJ 2017, Segmentation of fluorescence microscopy images using three dimensional active contours with inhomogeneity correction. in 2017 IEEE 14th International Symposium on Biomedical Imaging, ISBI 2017., 7950618, IEEE Computer Society, pp. 709-713, 14th IEEE International Symposium on Biomedical Imaging, ISBI 2017, Melbourne, Australia, 4/18/17. https://doi.org/10.1109/ISBI.2017.7950618
Lee S, Salama P, Dunn K, Delp EJ. Segmentation of fluorescence microscopy images using three dimensional active contours with inhomogeneity correction. In 2017 IEEE 14th International Symposium on Biomedical Imaging, ISBI 2017. IEEE Computer Society. 2017. p. 709-713. 7950618 https://doi.org/10.1109/ISBI.2017.7950618
Lee, Soonam ; Salama, Paul ; Dunn, Kenneth ; Delp, Edward J. / Segmentation of fluorescence microscopy images using three dimensional active contours with inhomogeneity correction. 2017 IEEE 14th International Symposium on Biomedical Imaging, ISBI 2017. IEEE Computer Society, 2017. pp. 709-713
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