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Proceedings Paper

Computer aided classification of cell nuclei in the gastrointestinal tract by volume and principal axis
Author(s): Ann M. Sagstetter; Jon J. Camp; Matthew S. Lurken; Joseph H. Szurszewski; Gianrico Farrugia; Simon J. Gibbons; Richard A. Robb
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Paper Abstract

Normal function of the gastrointestinal tract involves the coordinated activity of several cell types Human disorders of motor function of the gastrointestinal tract are often associated with changes in the number of these cells. For example, in diabetic patients, abnormalities in gastrointestinal transit are associated with changes in nerves and interstitial cells of Cajal (ICC), two key cells that generate and regulate motility. ICC are cells of mesenchymal origin that function as pacemakers and amplify neuronal signals in the gastrointestinal tract. Quantifying the changes in number of specific cell types in tissues from patients with motility disorders is challenging and requires immunolabeling for specific antigens. The shape of nuclei differs between the cell types in the wall of the gastrointestinal tract. Therefore the objective of this study was to determine whether cell nuclei can be classified by analyzing the 3D morphology of the nuclei. Furthermore, the orientation of the long axis of nuclei changes within and between the muscle layers. These features can be used to classify and differentially label the nuclei in confocal volume images of the tissue by computing the principal axis of the coordinates of the set of voxels forming each nucleus and thereby to identify cells by their nuclear morphology. Using this approach, we were able to separate and quantify nuclei in the smooth muscle layers of the tissue. Therefore we conclude that computer-aided classification of cell nuclei can be used to identify changes in the cell types expressed in gastrointestinal smooth muscle.

Paper Details

Date Published: 29 March 2007
PDF: 9 pages
Proc. SPIE 6514, Medical Imaging 2007: Computer-Aided Diagnosis, 65140E (29 March 2007); doi: 10.1117/12.710274
Show Author Affiliations
Ann M. Sagstetter, Mayo Clinic/Foundation (United States)
Jon J. Camp, Mayo Clinic/Foundation (United States)
Matthew S. Lurken, Mayo Clinic/Foundation (United States)
Joseph H. Szurszewski, Mayo Clinic/Foundation (United States)
Gianrico Farrugia, Mayo Clinic/Foundation (United States)
Simon J. Gibbons, Mayo Clinic/Foundation (United States)
Richard A. Robb, Mayo Clinic/Foundation (United States)

Published in SPIE Proceedings Vol. 6514:
Medical Imaging 2007: Computer-Aided Diagnosis
Maryellen L. Giger; Nico Karssemeijer, Editor(s)

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