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Authors: Viswanaath Subramanian 1 ; Randy H. Moss 1 ; Ryan K. Rader 2 ; Sneha K. Mahajan 1 and William V. Stoecker 3

Affiliations: 1 Missouri University of Science & Technology, United States ; 2 Stoecker & Associates, United States ; 3 Missouri University of Science & Technology and Stoecker & Associates, United States

ISBN: 978-989-8565-47-1

ISSN: 2184-4321

Keyword(s): Pattern Analysis, Image Processing, Object Detection, Template Matching, Seborrheic Keratosis, Milia-Like Cysts.

Related Ontology Subjects/Areas/Topics: Applications and Services ; Computer Vision, Visualization and Computer Graphics ; Features Extraction ; Image and Video Analysis ; Medical Image Applications ; Shape Representation and Matching

Abstract: Early detection of melanoma by magnified visible-light imaging (dermoscopy) is hindered by lesions which mimic melanoma. Automatic discrimination of melanoma from mimics could allow detection of melanoma at an earlier stage. Seborrheic keratoses are common mimics; these have distinctive bright structures: starry milia-like cysts (MLCs). We report discrimination of MLCs from mimics by features extracted from starry MLC (star) candidates. After pre-processing, 2D template matching is optimized with respect to star template size, histogram pre-processing, and 2D statistics. The novel aspects of this research were new details for region of interest (ROI) analysis of the centers of the star candidate, a new method for determining shape of hazy objects and multiple template matching, using unprocessed ROIs, shape-limited ROIs, and histogram-equalized ROIs. Features retained in the final model for the decision MLC vs. mimic by logistic regression include star size, 2D first correlation c oefficient, correlation coefficient to the star shape template, equalized correlation coefficient, relative star brightness, and statistical features at the star center. These methods allow optimization of MLC features found by 2D template correlation. This research confirms the importance of fine ROI features and ROI neighborhoods in medical imaging. (More)

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Paper citation in several formats:
Subramanian, V.; H. Moss, R.; K. Rader, R.; K. Mahajan, S. and V. Stoecker, W. (2013). Template Matching for Detection of Starry Milia-Like Cysts in Dermoscopic Images.In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2013) ISBN 978-989-8565-47-1, ISSN 2184-4321, pages 444-448. DOI: 10.5220/0004227504440448

@conference{visapp13,
author={Viswanaath Subramanian. and Randy H. Moss. and Ryan K. Rader. and Sneha K. Mahajan. and William V. Stoecker.},
title={Template Matching for Detection of Starry Milia-Like Cysts in Dermoscopic Images},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2013)},
year={2013},
pages={444-448},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004227504440448},
isbn={978-989-8565-47-1},
}

TY - CONF

JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2013)
TI - Template Matching for Detection of Starry Milia-Like Cysts in Dermoscopic Images
SN - 978-989-8565-47-1
AU - Subramanian, V.
AU - H. Moss, R.
AU - K. Rader, R.
AU - K. Mahajan, S.
AU - V. Stoecker, W.
PY - 2013
SP - 444
EP - 448
DO - 10.5220/0004227504440448

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