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Proceedings Paper

Automated ensemble segmentation of epithelial proliferation, necrosis, and fibrosis using scatter tumor imaging
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Paper Abstract

Conventional imaging systems used today in surgical settings rely on contrast enhancement based on color and intensity and they are not sensitive to morphology changes at the microscopic level. Elastic light scattering spectroscopy has been shown to distinguish ultra-structural changes in tissue. Therefore, it could provide this intrinsic contrast being enormously useful in guiding complex surgical interventions. Scatter parameters associated with epithelial proliferation, necrosis and fibrosis in pancreatic tumors were previously estimated in a quantitative manner. Subtle variations were encountered across the distinct diagnostic categories. This work proposes an automated methodology to correlate these variations with their corresponding tumor morphologies. A new approach based on the aggregation of the predictions of K-nearest neighbors (kNN) algorithm and Artificial Neural Networks (ANNs) has been developed. The major benefit obtained from the combination of the distinct classifiers is a significant increase in the number of pixel localizations whose corresponding tissue type is reliably assured. Pseudo-color diagnosis images are provided showing a strong correlation with sample segmentations performed by a veterinary pathologist.

Paper Details

Date Published: 17 May 2010
PDF: 10 pages
Proc. SPIE 7715, Biophotonics: Photonic Solutions for Better Health Care II, 77151B (17 May 2010); doi: 10.1117/12.854559
Show Author Affiliations
P. Beatriz Garcia-Allende, Univ. de Cantabria (Spain)
Olga M. Conde, Univ. de Cantabria (Spain)
Venkataramanan Krishnaswamy, Dartmouth College (United States)
P. Jack Hoopes, Dartmouth College (United States)
Dartmouth Hitchcock Medical Ctr. (United States)
Brian W. Pogue, Dartmouth College (United States)
Jesus Mirapeix, Univ. de Cantabria (Spain)
Jose M. Lopez-Higuera, Univ. de Cantabria (Spain)


Published in SPIE Proceedings Vol. 7715:
Biophotonics: Photonic Solutions for Better Health Care II
Jürgen Popp; Wolfgang Drexler; Valery V. Tuchin; Dennis L. Matthews, Editor(s)

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