Segmentation and analysis of insulin granule membranes in beta islet cell electron micrographs

David C Nam, Judith Mantell, David R Bull, Paul Verkade, Alin Achim

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

3 Citations (Scopus)

Abstract

Quantification of sub cellular structures is necessary in understanding how cells function. This paper presents a segmentation algorithm for transmission electron microscopy images of insulin granule membranes from beta cells of rat islet of Langerhans. Granules are described as having a dense core and a surrounding halo. We use a mixed vector field convolution snake to segment the granule membranes. We also present a novel contribution to the convergence filter family, which uses an adjustable region of support. The filter is used to verify our segmentation. We calculate pixel error by comparing the membrane areas from our method with a manually defined ground truth. 1300 granules are used in our test and an average area difference of 7.54% is observed.
Original languageEnglish
Title of host publication2012 Proceedings of the 20th European Signal Processing Conference (EUSIPCO 2012)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages2228-2232
Number of pages5
ISBN (Print)9781467310680
Publication statusPublished - Jan 2013
Event20th European Signal Processing Conference (EUSIPCO) - Bucharest, Romania
Duration: 27 Aug 201231 Aug 2012

Publication series

NameProceedings of the European Signal Processing Conference (EUSIPCO)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
ISSN (Print)2076-1465

Conference

Conference20th European Signal Processing Conference (EUSIPCO)
Country/TerritoryRomania
CityBucharest
Period27/08/1231/08/12

Fingerprint

Dive into the research topics of 'Segmentation and analysis of insulin granule membranes in beta islet cell electron micrographs'. Together they form a unique fingerprint.

Cite this