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Detection and density estimation of goblet cells in confocal endoscopy for the evaluation of celiac disease

Boschetto, Davide and Mirzaei, H. and Leong, R.W.L. and Grisan, Enrico Detection and density estimation of goblet cells in confocal endoscopy for the evaluation of celiac disease. In: 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, August 25-29, 2015, Milan pp. 6248-6251. ISBN 978-1-4244-9270-1. (2015)

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Abstract

Celiac Disease (CD) is an immune-mediated enteropathy, diagnosed in the clinical practice by intestinal biopsy and the concomitant presence of a positive celiac serology. Confocal Laser Endomicroscopy (CLE) allows skilled and trained experts to potentially perform in vivo virtual histology of small-bowel mucosa. In particular, it allows the qualitative evaluation of mucosa alteration such as a decrease in goblet cells density, presence of villous atrophy or crypt hypertrophy. We present a semi-automatic computer-based method for the detection of goblet cells from confocal endoscopy images, whose density changes in case of pathological tissue. After a manual selection of a suitable region of interest, the candidate columnar and goblet cells' centers are first detected and the cellular architecture is estimated from their position using a Voronoi diagram. The region within each Voronoi cell is then analyzed and classified as goblet cell or other. The results suggest that our method is able to detect and label goblet cells immersed in a columnar epithelium in a fast, reliable and automatic way. Accepting 0.44 false positives per image, we obtain a sensitivity value of 90.3. Furthermore, estimated and real goblet cell densities are comparable (error: 9.7 ± 16.9, correlation: 87.2, R2 = 76).

Item Type: Conference or Workshop Item (Paper)
Identification Number: https://doi.org/10.1109/EMBC.2015.7319820
Uncontrolled Keywords: Biological tissues, Biomedical optical imaging, Cellular biophysics, Endoscopes, Image classification, Laser applications in medicine, Medical image processing, Optical microscopy, Voronoi cell, Columnar epithelium, Confocal laser endomicroscopy, Crypt hypertrophy, Goblet cell density estimation.
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QH Natural history > QH301 Biology
T Technology > T Technology (General)
Research Area: Computer Science and Applications
Depositing User: Caterina Tangheroni
Date Deposited: 19 Jan 2016 15:31
Last Modified: 06 Apr 2016 07:34
URI: http://eprints.imtlucca.it/id/eprint/3017

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