Lezyon Kenarlarinin Fourier Tanimlayicilari Kullanilarak Cilt Lezyonlarinin Siniflandirilmasi

Enes Albay; Mustafa Kamaşak

doi:10.1109/TIPTEKNO.2015.7374547

Lezyon Kenarlarinin Fourier Tanimlayicilari Kullanilarak Cilt Lezyonlarinin Siniflandirilmasi

Translated title of the contribution: Skin lesion classification using fourier descriptors of lesion borders

Enes Albay, Mustafa Kamaşak

Department of Computer Engineering

Istanbul Technical University

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

7 Citations (Scopus)

Abstract

Between cancer types, Melanom is the one of the most deadliest form. Although, dermoscopy increased rate of diagnosis of the disease, most of the time detection of the disease depends on experience of physicist. There is great effort to diagnosis of the disease using computerized techniques. In this paper, for that purpose, we propose new method that uses fourier descriptors. After the segmentation of dermoscopic images, they are classified using extracted fourier descriptors of lesion border.

Translated title of the contribution	Skin lesion classification using fourier descriptors of lesion borders
Original language	Turkish
Title of host publication	2015 Medical Technologies National Conference, TIPTEKNO 2015
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781467377652
DOIs	https://doi.org/10.1109/TIPTEKNO.2015.7374547
Publication status	Published - 6 Jan 2016
Event	Medical Technologies National Conference, TIPTEKNO 2015 - Bodrum, Turkey Duration: 15 Oct 2015 → 18 Oct 2015

Publication series

Name	2015 Medical Technologies National Conference, TIPTEKNO 2015

Conference

Conference	Medical Technologies National Conference, TIPTEKNO 2015
Country/Territory	Turkey
City	Bodrum
Period	15/10/15 → 18/10/15

Bibliographical note

Publisher Copyright:
© 2015 IEEE.

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10.1109/TIPTEKNO.2015.7374547

Cite this

Albay, E., & Kamaşak, M. (2016). Lezyon Kenarlarinin Fourier Tanimlayicilari Kullanilarak Cilt Lezyonlarinin Siniflandirilmasi. In 2015 Medical Technologies National Conference, TIPTEKNO 2015 Article 7374547 (2015 Medical Technologies National Conference, TIPTEKNO 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/TIPTEKNO.2015.7374547

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title = "Lezyon Kenarlarinin Fourier Tanimlayicilari Kullanilarak Cilt Lezyonlarinin Siniflandirilmasi",

abstract = "Between cancer types, Melanom is the one of the most deadliest form. Although, dermoscopy increased rate of diagnosis of the disease, most of the time detection of the disease depends on experience of physicist. There is great effort to diagnosis of the disease using computerized techniques. In this paper, for that purpose, we propose new method that uses fourier descriptors. After the segmentation of dermoscopic images, they are classified using extracted fourier descriptors of lesion border.",

keywords = "artificial neural networks, classification, dermoscopy, fourier descriptors, melanoma",

author = "Enes Albay and Mustafa Kama{\c s}ak",

note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; Medical Technologies National Conference, TIPTEKNO 2015 ; Conference date: 15-10-2015 Through 18-10-2015",

year = "2016",

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Albay, E & Kamaşak, M 2016, Lezyon Kenarlarinin Fourier Tanimlayicilari Kullanilarak Cilt Lezyonlarinin Siniflandirilmasi. in 2015 Medical Technologies National Conference, TIPTEKNO 2015., 7374547, 2015 Medical Technologies National Conference, TIPTEKNO 2015, Institute of Electrical and Electronics Engineers Inc., Medical Technologies National Conference, TIPTEKNO 2015, Bodrum, Turkey, 15/10/15. https://doi.org/10.1109/TIPTEKNO.2015.7374547

Lezyon Kenarlarinin Fourier Tanimlayicilari Kullanilarak Cilt Lezyonlarinin Siniflandirilmasi. / Albay, Enes; Kamaşak, Mustafa.
2015 Medical Technologies National Conference, TIPTEKNO 2015. Institute of Electrical and Electronics Engineers Inc., 2016. 7374547 (2015 Medical Technologies National Conference, TIPTEKNO 2015).

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

TY - GEN

T1 - Lezyon Kenarlarinin Fourier Tanimlayicilari Kullanilarak Cilt Lezyonlarinin Siniflandirilmasi

AU - Albay, Enes

AU - Kamaşak, Mustafa

PY - 2016/1/6

Y1 - 2016/1/6

N2 - Between cancer types, Melanom is the one of the most deadliest form. Although, dermoscopy increased rate of diagnosis of the disease, most of the time detection of the disease depends on experience of physicist. There is great effort to diagnosis of the disease using computerized techniques. In this paper, for that purpose, we propose new method that uses fourier descriptors. After the segmentation of dermoscopic images, they are classified using extracted fourier descriptors of lesion border.

AB - Between cancer types, Melanom is the one of the most deadliest form. Although, dermoscopy increased rate of diagnosis of the disease, most of the time detection of the disease depends on experience of physicist. There is great effort to diagnosis of the disease using computerized techniques. In this paper, for that purpose, we propose new method that uses fourier descriptors. After the segmentation of dermoscopic images, they are classified using extracted fourier descriptors of lesion border.

KW - artificial neural networks

KW - classification

KW - dermoscopy

KW - fourier descriptors

KW - melanoma

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U2 - 10.1109/TIPTEKNO.2015.7374547

DO - 10.1109/TIPTEKNO.2015.7374547

M3 - Konferans katkısı

AN - SCOPUS:84964255571

T3 - 2015 Medical Technologies National Conference, TIPTEKNO 2015

BT - 2015 Medical Technologies National Conference, TIPTEKNO 2015

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - Medical Technologies National Conference, TIPTEKNO 2015

Y2 - 15 October 2015 through 18 October 2015

ER -

Lezyon Kenarlarinin Fourier Tanimlayicilari Kullanilarak Cilt Lezyonlarinin Siniflandirilmasi

Abstract

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Conference

Bibliographical note

UN SDGs

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