Jelly filling segmentation of fluorescence microscopy images containing incomplete labeling

Neeraj J. Gadgil, Paul Salama, Kenneth Dunn, Edward J. Delp

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

3 Citations (Scopus)

Abstract

Biological images acquired using fluorescence microscopy typically suffer from poor edge details, non-uniform brightness, decreasing image contrast with tissue depth and irregular/unknown structure. Hence they are consequently challenging to segment. In this paper, we present a segmentation method we call «Jelly filling» for analyzing biological volumes that also contain incomplete labeling. Our method uses adaptive thresholding, component analysis, and three-dimensional structural consistency to iteratively refine segments that represent physical quantities. Preliminary results obtained using fluorescence microscopy images of rat kidneys demonstrate the efficacy of the proposed method.

Original languageEnglish (US)
Title of host publication2016 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2016 - Proceedings
PublisherIEEE Computer Society
Pages531-535
Number of pages5
Volume2016-June
ISBN (Electronic)9781479923502
DOIs
StatePublished - Jun 15 2016
Event2016 IEEE 13th International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2016 - Prague, Czech Republic
Duration: Apr 13 2016Apr 16 2016

Other

Other2016 IEEE 13th International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2016
CountryCzech Republic
CityPrague
Period4/13/164/16/16

Fingerprint

Fluorescence microscopy
Fluorescence Microscopy
Labeling
Rats
Luminance
Tissue
Kidney

Keywords

  • fluorescence microscopy
  • image segmentation

ASJC Scopus subject areas

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

Cite this

Gadgil, N. J., Salama, P., Dunn, K., & Delp, E. J. (2016). Jelly filling segmentation of fluorescence microscopy images containing incomplete labeling. In 2016 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2016 - Proceedings (Vol. 2016-June, pp. 531-535). [7493324] IEEE Computer Society. https://doi.org/10.1109/ISBI.2016.7493324

Jelly filling segmentation of fluorescence microscopy images containing incomplete labeling. / Gadgil, Neeraj J.; Salama, Paul; Dunn, Kenneth; Delp, Edward J.

2016 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2016 - Proceedings. Vol. 2016-June IEEE Computer Society, 2016. p. 531-535 7493324.

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

Gadgil, NJ, Salama, P, Dunn, K & Delp, EJ 2016, Jelly filling segmentation of fluorescence microscopy images containing incomplete labeling. in 2016 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2016 - Proceedings. vol. 2016-June, 7493324, IEEE Computer Society, pp. 531-535, 2016 IEEE 13th International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2016, Prague, Czech Republic, 4/13/16. https://doi.org/10.1109/ISBI.2016.7493324
Gadgil NJ, Salama P, Dunn K, Delp EJ. Jelly filling segmentation of fluorescence microscopy images containing incomplete labeling. In 2016 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2016 - Proceedings. Vol. 2016-June. IEEE Computer Society. 2016. p. 531-535. 7493324 https://doi.org/10.1109/ISBI.2016.7493324
Gadgil, Neeraj J. ; Salama, Paul ; Dunn, Kenneth ; Delp, Edward J. / Jelly filling segmentation of fluorescence microscopy images containing incomplete labeling. 2016 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2016 - Proceedings. Vol. 2016-June IEEE Computer Society, 2016. pp. 531-535
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