Artifact removal and lesion segmentation for melanoma detection in skin lesion images

Julie Ann Salido; Conrado Ruiz; Nelson Marcos

Artifact removal and lesion segmentation for melanoma detection in skin lesion images

Julie Ann Salido
, Conrado Ruiz
, Nelson Marcos

Research output: Book chapter › Conference contribution › peer-review

Abstract

Melanoma is a severe form of skin cancer characterized by the rapid multiplication of pigment-producing cells. There are new techniques for automated analysis of skin lesions for classification of melanoma using images from digital cameras and smart phones. A problem on analysis of these images are interesting because of the existence of artifacts and noise such as hair, veins, water residue, illuminations and light reflections. An important step in the diagnosis of melanoma is the removal of artifacts and reduction of noise that can inhibit the examination to accurately segment the skin lesion from the surrounding skin area. In this paper, a new method for extraction of skin lesion is implemented based on image enhancement and morphological operators. The experimental results show that artifact removal and lesion segmentation in skin lesion images can perform a true detection rate of 95.37% for melanoma skin lesion segmentation.

Original language	English
Title of host publication	MCCSIS 2018 - Multi Conference on Computer Science and Information Systems; Proceedings of the International Conferences on Interfaces and Human Computer Interaction 2018, Game and Entertainment Technologies 2018 and Computer Graphics, Visualization, Computer Vision and Image Processing 2018
Editors	Katherine Blashki, Luis Rodrigues, Yingcai Xiao
Publisher	IADIS
Pages	392-396
Number of pages	5
ISBN (Print)	9789898533791
Publication status	Published - 2018
Externally published	Yes
Event	12th International Conference on Interfaces and Human Computer Interaction 2018, 11th International Conference on Game and Entertainment Technologies 2018 and 12th International Conference on Computer Graphics, Visualization, Computer Vision and Image Processing 2018, part of the Multi Conference on Computer Science and Information Systems 2018, MCCSIS 2018 - Madrid, Spain Duration: 18 Jul 2018 → 20 Jul 2018

Publication series

Name	MCCSIS 2018 - Multi Conference on Computer Science and Information Systems; Proceedings of the International Conferences on Interfaces and Human Computer Interaction 2018, Game and Entertainment Technologies 2018 and Computer Graphics, Visualization, Computer Vision and Image Processing 2018
Volume	2018-July

Conference

Conference	12th International Conference on Interfaces and Human Computer Interaction 2018, 11th International Conference on Game and Entertainment Technologies 2018 and 12th International Conference on Computer Graphics, Visualization, Computer Vision and Image Processing 2018, part of the Multi Conference on Computer Science and Information Systems 2018, MCCSIS 2018
Country/Territory	Spain
City	Madrid
Period	18/07/18 → 20/07/18

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Artifacts Removal
Lesion Segmentation
Melanoma

Cite this

Salido, J. A., Ruiz, C., & Marcos, N. (2018). Artifact removal and lesion segmentation for melanoma detection in skin lesion images. In K. Blashki, L. Rodrigues, & Y. Xiao (Eds.), MCCSIS 2018 - Multi Conference on Computer Science and Information Systems; Proceedings of the International Conferences on Interfaces and Human Computer Interaction 2018, Game and Entertainment Technologies 2018 and Computer Graphics, Visualization, Computer Vision and Image Processing 2018 (pp. 392-396). (MCCSIS 2018 - Multi Conference on Computer Science and Information Systems; Proceedings of the International Conferences on Interfaces and Human Computer Interaction 2018, Game and Entertainment Technologies 2018 and Computer Graphics, Visualization, Computer Vision and Image Processing 2018; Vol. 2018-July). IADIS.

Salido, Julie Ann ; Ruiz, Conrado ; Marcos, Nelson. / Artifact removal and lesion segmentation for melanoma detection in skin lesion images. MCCSIS 2018 - Multi Conference on Computer Science and Information Systems; Proceedings of the International Conferences on Interfaces and Human Computer Interaction 2018, Game and Entertainment Technologies 2018 and Computer Graphics, Visualization, Computer Vision and Image Processing 2018. editor / Katherine Blashki ; Luis Rodrigues ; Yingcai Xiao. IADIS, 2018. pp. 392-396 (MCCSIS 2018 - Multi Conference on Computer Science and Information Systems; Proceedings of the International Conferences on Interfaces and Human Computer Interaction 2018, Game and Entertainment Technologies 2018 and Computer Graphics, Visualization, Computer Vision and Image Processing 2018).

@inproceedings{ce30fd66f1c547f9bedc34f882872aca,

title = "Artifact removal and lesion segmentation for melanoma detection in skin lesion images",

abstract = "Melanoma is a severe form of skin cancer characterized by the rapid multiplication of pigment-producing cells. There are new techniques for automated analysis of skin lesions for classification of melanoma using images from digital cameras and smart phones. A problem on analysis of these images are interesting because of the existence of artifacts and noise such as hair, veins, water residue, illuminations and light reflections. An important step in the diagnosis of melanoma is the removal of artifacts and reduction of noise that can inhibit the examination to accurately segment the skin lesion from the surrounding skin area. In this paper, a new method for extraction of skin lesion is implemented based on image enhancement and morphological operators. The experimental results show that artifact removal and lesion segmentation in skin lesion images can perform a true detection rate of 95.37\% for melanoma skin lesion segmentation.",

keywords = "Artifacts Removal, Lesion Segmentation, Melanoma",

author = "Salido, \{Julie Ann\} and Conrado Ruiz and Nelson Marcos",

note = "Publisher Copyright: {\textcopyright} 2018.; 12th International Conference on Interfaces and Human Computer Interaction 2018, 11th International Conference on Game and Entertainment Technologies 2018 and 12th International Conference on Computer Graphics, Visualization, Computer Vision and Image Processing 2018, part of the Multi Conference on Computer Science and Information Systems 2018, MCCSIS 2018 ; Conference date: 18-07-2018 Through 20-07-2018",

year = "2018",

language = "English",

isbn = "9789898533791",

series = "MCCSIS 2018 - Multi Conference on Computer Science and Information Systems; Proceedings of the International Conferences on Interfaces and Human Computer Interaction 2018, Game and Entertainment Technologies 2018 and Computer Graphics, Visualization, Computer Vision and Image Processing 2018",

publisher = "IADIS",

pages = "392--396",

editor = "Katherine Blashki and Luis Rodrigues and Yingcai Xiao",

booktitle = "MCCSIS 2018 - Multi Conference on Computer Science and Information Systems; Proceedings of the International Conferences on Interfaces and Human Computer Interaction 2018, Game and Entertainment Technologies 2018 and Computer Graphics, Visualization, Computer Vision and Image Processing 2018",

}

Salido, JA, Ruiz, C & Marcos, N 2018, Artifact removal and lesion segmentation for melanoma detection in skin lesion images. in K Blashki, L Rodrigues & Y Xiao (eds), MCCSIS 2018 - Multi Conference on Computer Science and Information Systems; Proceedings of the International Conferences on Interfaces and Human Computer Interaction 2018, Game and Entertainment Technologies 2018 and Computer Graphics, Visualization, Computer Vision and Image Processing 2018. MCCSIS 2018 - Multi Conference on Computer Science and Information Systems; Proceedings of the International Conferences on Interfaces and Human Computer Interaction 2018, Game and Entertainment Technologies 2018 and Computer Graphics, Visualization, Computer Vision and Image Processing 2018, vol. 2018-July, IADIS, pp. 392-396, 12th International Conference on Interfaces and Human Computer Interaction 2018, 11th International Conference on Game and Entertainment Technologies 2018 and 12th International Conference on Computer Graphics, Visualization, Computer Vision and Image Processing 2018, part of the Multi Conference on Computer Science and Information Systems 2018, MCCSIS 2018, Madrid, Spain, 18/07/18.

Artifact removal and lesion segmentation for melanoma detection in skin lesion images. / Salido, Julie Ann; Ruiz, Conrado; Marcos, Nelson.
MCCSIS 2018 - Multi Conference on Computer Science and Information Systems; Proceedings of the International Conferences on Interfaces and Human Computer Interaction 2018, Game and Entertainment Technologies 2018 and Computer Graphics, Visualization, Computer Vision and Image Processing 2018. ed. / Katherine Blashki; Luis Rodrigues; Yingcai Xiao. IADIS, 2018. p. 392-396 (MCCSIS 2018 - Multi Conference on Computer Science and Information Systems; Proceedings of the International Conferences on Interfaces and Human Computer Interaction 2018, Game and Entertainment Technologies 2018 and Computer Graphics, Visualization, Computer Vision and Image Processing 2018; Vol. 2018-July).

Research output: Book chapter › Conference contribution › peer-review

TY - GEN

T1 - Artifact removal and lesion segmentation for melanoma detection in skin lesion images

AU - Salido, Julie Ann

AU - Ruiz, Conrado

AU - Marcos, Nelson

PY - 2018

Y1 - 2018

N2 - Melanoma is a severe form of skin cancer characterized by the rapid multiplication of pigment-producing cells. There are new techniques for automated analysis of skin lesions for classification of melanoma using images from digital cameras and smart phones. A problem on analysis of these images are interesting because of the existence of artifacts and noise such as hair, veins, water residue, illuminations and light reflections. An important step in the diagnosis of melanoma is the removal of artifacts and reduction of noise that can inhibit the examination to accurately segment the skin lesion from the surrounding skin area. In this paper, a new method for extraction of skin lesion is implemented based on image enhancement and morphological operators. The experimental results show that artifact removal and lesion segmentation in skin lesion images can perform a true detection rate of 95.37% for melanoma skin lesion segmentation.

AB - Melanoma is a severe form of skin cancer characterized by the rapid multiplication of pigment-producing cells. There are new techniques for automated analysis of skin lesions for classification of melanoma using images from digital cameras and smart phones. A problem on analysis of these images are interesting because of the existence of artifacts and noise such as hair, veins, water residue, illuminations and light reflections. An important step in the diagnosis of melanoma is the removal of artifacts and reduction of noise that can inhibit the examination to accurately segment the skin lesion from the surrounding skin area. In this paper, a new method for extraction of skin lesion is implemented based on image enhancement and morphological operators. The experimental results show that artifact removal and lesion segmentation in skin lesion images can perform a true detection rate of 95.37% for melanoma skin lesion segmentation.

KW - Artifacts Removal

KW - Lesion Segmentation

KW - Melanoma

UR - https://www.scopus.com/pages/publications/85063129233

M3 - Conference contribution

AN - SCOPUS:85063129233

SN - 9789898533791

T3 - MCCSIS 2018 - Multi Conference on Computer Science and Information Systems; Proceedings of the International Conferences on Interfaces and Human Computer Interaction 2018, Game and Entertainment Technologies 2018 and Computer Graphics, Visualization, Computer Vision and Image Processing 2018

SP - 392

EP - 396

BT - MCCSIS 2018 - Multi Conference on Computer Science and Information Systems; Proceedings of the International Conferences on Interfaces and Human Computer Interaction 2018, Game and Entertainment Technologies 2018 and Computer Graphics, Visualization, Computer Vision and Image Processing 2018

A2 - Blashki, Katherine

A2 - Rodrigues, Luis

A2 - Xiao, Yingcai

PB - IADIS

T2 - 12th International Conference on Interfaces and Human Computer Interaction 2018, 11th International Conference on Game and Entertainment Technologies 2018 and 12th International Conference on Computer Graphics, Visualization, Computer Vision and Image Processing 2018, part of the Multi Conference on Computer Science and Information Systems 2018, MCCSIS 2018

Y2 - 18 July 2018 through 20 July 2018

ER -

Salido JA, Ruiz C, Marcos N. Artifact removal and lesion segmentation for melanoma detection in skin lesion images. In Blashki K, Rodrigues L, Xiao Y, editors, MCCSIS 2018 - Multi Conference on Computer Science and Information Systems; Proceedings of the International Conferences on Interfaces and Human Computer Interaction 2018, Game and Entertainment Technologies 2018 and Computer Graphics, Visualization, Computer Vision and Image Processing 2018. IADIS. 2018. p. 392-396. (MCCSIS 2018 - Multi Conference on Computer Science and Information Systems; Proceedings of the International Conferences on Interfaces and Human Computer Interaction 2018, Game and Entertainment Technologies 2018 and Computer Graphics, Visualization, Computer Vision and Image Processing 2018).

Artifact removal and lesion segmentation for melanoma detection in skin lesion images

Abstract

Publication series

Conference

UN SDGs

Keywords

Other files and links

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Cite this