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Depth Data Improves Skin Lesion Segmentation

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Original languageEnglish
Title of host publicationMedical Image Computing and Computer-Assisted Intervention ? MICCAI 2009
Subtitle of host publication12th International Conference, London, UK, September 20-24, 2009, Proceedings, Part II
EditorsGuang-Zhong Yang, David Hawkes, Daniel Rueckert, Alison Noble, Chris Taylor
PublisherSpringer-Verlag GmbH
Pages1100-1107
Number of pages8
ISBN (Print)978-3-642-04270-6
DOIs
Publication statusPublished - 2009

Publication series

NameLecture Notes in Computer Science
PublisherSpringer Berlin / Heidelberg
Volume5762
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Abstract

This paper shows that adding 3D depth information to RGB colour images improves segmentation of pigmented and non-pigmented skin lesion. A region-based active contour segmentation approach using a statistical model based on the level-set framework is presented. We consider what kinds of properties (e.g., colour, depth, texture) are most discriminative. The experiments show that our proposed method integrating chromatic and geometric information produces segmentation results for pigmented lesions close to dermatologists and more consistent and accurate results for non-pigmented lesions.

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