NDLI: A robust hair segmentation and removal approach for clinical images of skin lesions

Content Provider	IEEE Xplore Digital Library
Author	Huang, A. Shun-Yuen Kwan Wen-Yu Chang Min-Yin Liu Min-Hsiu Chi Gwo-Shing Chen
Copyright Year	2013
Description	Author affiliation: E-Da Hosp., I-Shou Univ., Kaohsiung, Taiwan (Wen-Yu Chang) \|\| Res. Center for Adaptive Data Anal./Center for Dynamical Biomarkers & Translational Med./Grad. Inst. of Biomed. Eng., Nat. Central Univ., Jhongli, Taiwan (Huang, A.) \|\| Inst. of Syst. Biol. & Bioinf., Nat. Central Univ., Jhongli, Taiwan (Shun-Yuen Kwan; Min-Yin Liu; Min-Hsiu Chi) \|\| Dept. of Dermatology, Kaohsiung Med. Univ. Hosp., Kaohsiung, Taiwan (Gwo-Shing Chen)
Abstract	Artifacts such as hair are major obstacles to automatic segmentation of pigmented skin lesion images for computer-aided diagnosis systems. It is even more challenging to process clinical images taken by a regular digital camera, where the shadows of the skin texture may mimic hair-like curvilinear structures. In this study, we examined the popular DullRazor software with a dataset of 20 clinical images. The software, specifically designed for dermoscopic images, was unable to remove fine hairs or hairs in the shade. Alternatively, we proposed using conventional matched filters to enhance curvilinear structures. The more complicate hair intersection patterns, which were known to generate low matched filtering responses, were recovered by using region growing algorithms from nearby detected hair segments with linear discriminant analysis (LDA) based on a color similarity criterion. The preliminary results indicated the proposed method was able to remove more fine hairs and hairs in the shade, and lower false hair detection rate by 58% (from 0.438 to 0.183) as compared to the DullRazor's approach.
Starting Page	3315
Ending Page	3318
File Size	1050769
Page Count	4
File Format	PDF
ISBN	9781457702167
ISSN	1557170X
DOI	10.1109/EMBC.2013.6610250
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-07-03
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Hair Lesions Skin Image color analysis Biomedical imaging Image segmentation Matched filters
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

VirtualShave: Automated hair removal from digital dermatoscopic images

Determination of border irregularity in dermoscopic color images of pigmented skin lesions

Automated saliency-based lesion segmentation in dermoscopic images

Lesion border detection in Buruli ulcer images

Statistical characterization and segmentation of drusen in fundus images

Detecting the pigment network in dermoscopy images: A directional approach

Early melanoma diagnosis with mobile imaging

Robust supervised segmentation of neuropathology whole-slide microscopy images

Computer aided analysis of epi-illumination and transillumination images of skin lesions for diagnosis of skin cancers

A robust hair segmentation and removal approach for clinical images of skin lesions

Similar Documents

VirtualShave: Automated hair removal from digital dermatoscopic images

Determination of border irregularity in dermoscopic color images of pigmented skin lesions

Automated saliency-based lesion segmentation in dermoscopic images

Lesion border detection in Buruli ulcer images

Statistical characterization and segmentation of drusen in fundus images

Detecting the pigment network in dermoscopy images: A directional approach

Early melanoma diagnosis with mobile imaging

Robust supervised segmentation of neuropathology whole-slide microscopy images

Computer aided analysis of epi-illumination and transillumination images of skin lesions for diagnosis of skin cancers

A robust hair segmentation and removal approach for clinical images of skin lesions