Improving skin lesion segmentation in dermoscopic images by thin artefacts removal methods
2016 (English)In: Proceedings Of The 2016 6th European Workshop On Visual Information Processing (EUVIP) / [ed] Beghdadi, A; Bourennane, S; Bouzerdoum, A; Pedersen, M; Oudre, L; Jiang, R, 2016Conference paper, Published paper (Refereed)
Abstract [en]
In dermoscopic images, various thin artefacts naturally appear, most usually in the form of hairs. While trying to find the border of the skin lesion, these artefacts affect the lesion segmentation methods and also the subsequent classification.Currently, there is a lot of research focus in this area and various methods are presented both for skin lesion segmentation and thin artefacts removal. In this paper, we investigate into three different thin artefacts removal methods and compare their results using two different skin lesion segmentation methods. The segmentation results are compared with groundtruth segmentation. In addition, we introduce our novel artefacts removal method, which combined with the ExpectationMaximization image segmentation outperforms all the tested methods.
Place, publisher, year, edition, pages
2016.
Keywords [en]
thin artefacts removal, skin lesion seg- mentation, dermoscopic images, Chan-Vese segmentation, expectation-maximization segmentation
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:uu:diva-306892ISI: 000391630800001ISBN: 9781509027811 (print)OAI: oai:DiVA.org:uu-306892DiVA, id: diva2:1044666
Conference
The 6th European Workshop on Visual Information Processing (EUVIP 2016) Marseille, FRANCE, OCT 25-27, 2016
Funder
Swedish Research Council, 621-2014-61532016-11-042016-11-042018-01-13Bibliographically approved