Pigment network-based skin cancer detection

Naser Alfed; Fouad Khelifi; Ahmed Bouridane; Huseyin Seker

doi:10.1109/EMBC.2015.7320056

Pigment network-based skin cancer detection

Naser Alfed, Fouad Khelifi, Ahmed Bouridane, Huseyin Seker

Computer and Information Sciences Department

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

29 Citations (Scopus)

Abstract

Diagnosing skin cancer in its early stages is a challenging task for dermatologists given the fact that the chance for a patient's survival is higher and hence the process of analyzing skin images and making decisions should be time efficient. Therefore, diagnosing the disease using automated and computerized systems has nowadays become essential. This paper proposes an efficient system for skin cancer detection on dermoscopic images. It has been shown that the statistical characteristics of the pigment network, extracted from the dermoscopic image, could be used as efficient discriminating features for cancer detection. The proposed system has been assessed on a dataset of 200 dermoscopic images of the 'Hospital Pedro Hispano' [1] and the results of cross-validation have shown high detection accuracy.

Original language	English
Title of host publication	2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	7214-7217
Number of pages	4
ISBN (Electronic)	9781424492718
DOIs	https://doi.org/10.1109/EMBC.2015.7320056
Publication status	Published - 5 Nov 2015
Event	37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015 - Milan, Italy Duration: 25 Aug 2015 → 29 Aug 2015

Conference

Conference	37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
Country/Territory	Italy
City	Milan
Period	25/08/15 → 29/08/15

Keywords

dermoscopic image
Pigment network detection

UN SDGs

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

Access to Document

10.1109/EMBC.2015.7320056

Cite this

@inproceedings{8a176fc9bccc4b37bbcf17d393a04b50,

title = "Pigment network-based skin cancer detection",

abstract = "Diagnosing skin cancer in its early stages is a challenging task for dermatologists given the fact that the chance for a patient's survival is higher and hence the process of analyzing skin images and making decisions should be time efficient. Therefore, diagnosing the disease using automated and computerized systems has nowadays become essential. This paper proposes an efficient system for skin cancer detection on dermoscopic images. It has been shown that the statistical characteristics of the pigment network, extracted from the dermoscopic image, could be used as efficient discriminating features for cancer detection. The proposed system has been assessed on a dataset of 200 dermoscopic images of the 'Hospital Pedro Hispano' [1] and the results of cross-validation have shown high detection accuracy.",

keywords = "dermoscopic image, Pigment network detection",

author = "Naser Alfed and Fouad Khelifi and Ahmed Bouridane and Huseyin Seker",

year = "2015",

month = nov,

day = "5",

doi = "10.1109/EMBC.2015.7320056",

language = "English",

pages = "7214--7217",

booktitle = "2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

address = "United States",

note = "37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015 ; Conference date: 25-08-2015 Through 29-08-2015",

}

Alfed, N, Khelifi, F, Bouridane, A & Seker, H 2015, Pigment network-based skin cancer detection. in 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015. Institute of Electrical and Electronics Engineers Inc., pp. 7214-7217, 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015, Milan, Italy, 25/08/15. https://doi.org/10.1109/EMBC.2015.7320056

Pigment network-based skin cancer detection. / Alfed, Naser; Khelifi, Fouad; Bouridane, Ahmed et al.
2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015. Institute of Electrical and Electronics Engineers Inc., 2015. p. 7214-7217.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Pigment network-based skin cancer detection

AU - Alfed, Naser

AU - Khelifi, Fouad

AU - Bouridane, Ahmed

AU - Seker, Huseyin

PY - 2015/11/5

Y1 - 2015/11/5

N2 - Diagnosing skin cancer in its early stages is a challenging task for dermatologists given the fact that the chance for a patient's survival is higher and hence the process of analyzing skin images and making decisions should be time efficient. Therefore, diagnosing the disease using automated and computerized systems has nowadays become essential. This paper proposes an efficient system for skin cancer detection on dermoscopic images. It has been shown that the statistical characteristics of the pigment network, extracted from the dermoscopic image, could be used as efficient discriminating features for cancer detection. The proposed system has been assessed on a dataset of 200 dermoscopic images of the 'Hospital Pedro Hispano' [1] and the results of cross-validation have shown high detection accuracy.

AB - Diagnosing skin cancer in its early stages is a challenging task for dermatologists given the fact that the chance for a patient's survival is higher and hence the process of analyzing skin images and making decisions should be time efficient. Therefore, diagnosing the disease using automated and computerized systems has nowadays become essential. This paper proposes an efficient system for skin cancer detection on dermoscopic images. It has been shown that the statistical characteristics of the pigment network, extracted from the dermoscopic image, could be used as efficient discriminating features for cancer detection. The proposed system has been assessed on a dataset of 200 dermoscopic images of the 'Hospital Pedro Hispano' [1] and the results of cross-validation have shown high detection accuracy.

KW - dermoscopic image

KW - Pigment network detection

U2 - 10.1109/EMBC.2015.7320056

DO - 10.1109/EMBC.2015.7320056

M3 - Conference contribution

C2 - 26737956

AN - SCOPUS:84953310825

SP - 7214

EP - 7217

BT - 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015

Y2 - 25 August 2015 through 29 August 2015

ER -

Pigment network-based skin cancer detection

Abstract

Conference

Keywords

UN SDGs

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Cite this