Determining the asymmetries of skin lesions with fuzzy borders

Vincent To Yee Ng; Tim Lee; Benny Y.M. Fung

doi:10.1109/BIBE.2003.1188955

Determining the asymmetries of skin lesions with fuzzy borders

Vincent To Yee Ng
, Tim Lee
, Benny Y.M. Fung

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

2 Citations (Scopus)

Abstract

Malignant melanoma is a popular cancer among youth; it is desirable to have a fast and convenience way to determine this disease in its early stage. One of the clinical features in diagnosis is related to the shape of lesions. In previous studies, circularity is commonly used as the asymmetric measurement of skin lesions. However, this measurement depends very much on the accuracy of the segmentation result. In this paper, we present an artificial neural network model to improve the measurements of the asymmetries of lesions that may have fuzzy borders. The main idea is enhancing the symmetric distant (eSD) with a number of variations. Results from experiments, which use the digitized images from the Lesion Clinic in Vancouver, Canada have shown the good discriminating power of the neural network model.

Original language	English
Title of host publication	Proceedings - 3rd IEEE Symposium on BioInformatics and BioEngineering, BIBE 2003
Publisher	IEEE
Pages	223-230
Number of pages	8
ISBN (Electronic)	0769519075, 9780769519074
DOIs	https://doi.org/10.1109/BIBE.2003.1188955
Publication status	Published - 1 Jan 2003
Event	3rd IEEE Symposium on BioInformatics and BioEngineering, BIBE 2003 - Bethesda, United States Duration: 10 Mar 2003 → 12 Mar 2003

Conference

Conference	3rd IEEE Symposium on BioInformatics and BioEngineering, BIBE 2003
Country/Territory	United States
City	Bethesda
Period	10/03/03 → 12/03/03

UN SDGs

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

SDG 3 Good Health and Well-being

ASJC Scopus subject areas

Computer Networks and Communications
Signal Processing
Electrical and Electronic Engineering

More information

10.1109/BIBE.2003.1188955

Cite this

@inproceedings{a40570b23db845aeafec724b0ff0895c,

title = "Determining the asymmetries of skin lesions with fuzzy borders",

abstract = "Malignant melanoma is a popular cancer among youth; it is desirable to have a fast and convenience way to determine this disease in its early stage. One of the clinical features in diagnosis is related to the shape of lesions. In previous studies, circularity is commonly used as the asymmetric measurement of skin lesions. However, this measurement depends very much on the accuracy of the segmentation result. In this paper, we present an artificial neural network model to improve the measurements of the asymmetries of lesions that may have fuzzy borders. The main idea is enhancing the symmetric distant (eSD) with a number of variations. Results from experiments, which use the digitized images from the Lesion Clinic in Vancouver, Canada have shown the good discriminating power of the neural network model.",

author = "Ng, \{Vincent To Yee\} and Tim Lee and Fung, \{Benny Y.M.\}",

year = "2003",

month = jan,

day = "1",

doi = "10.1109/BIBE.2003.1188955",

language = "English",

pages = "223--230",

booktitle = "Proceedings - 3rd IEEE Symposium on BioInformatics and BioEngineering, BIBE 2003",

publisher = "IEEE",

address = "United States",

note = "3rd IEEE Symposium on BioInformatics and BioEngineering, BIBE 2003 ; Conference date: 10-03-2003 Through 12-03-2003",

}

Determining the asymmetries of skin lesions with fuzzy borders. / Ng, Vincent To Yee; Lee, Tim; Fung, Benny Y.M.
Proceedings - 3rd IEEE Symposium on BioInformatics and BioEngineering, BIBE 2003. IEEE, 2003. p. 223-230 1188955.

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

TY - GEN

T1 - Determining the asymmetries of skin lesions with fuzzy borders

AU - Ng, Vincent To Yee

AU - Lee, Tim

AU - Fung, Benny Y.M.

PY - 2003/1/1

Y1 - 2003/1/1

N2 - Malignant melanoma is a popular cancer among youth; it is desirable to have a fast and convenience way to determine this disease in its early stage. One of the clinical features in diagnosis is related to the shape of lesions. In previous studies, circularity is commonly used as the asymmetric measurement of skin lesions. However, this measurement depends very much on the accuracy of the segmentation result. In this paper, we present an artificial neural network model to improve the measurements of the asymmetries of lesions that may have fuzzy borders. The main idea is enhancing the symmetric distant (eSD) with a number of variations. Results from experiments, which use the digitized images from the Lesion Clinic in Vancouver, Canada have shown the good discriminating power of the neural network model.

AB - Malignant melanoma is a popular cancer among youth; it is desirable to have a fast and convenience way to determine this disease in its early stage. One of the clinical features in diagnosis is related to the shape of lesions. In previous studies, circularity is commonly used as the asymmetric measurement of skin lesions. However, this measurement depends very much on the accuracy of the segmentation result. In this paper, we present an artificial neural network model to improve the measurements of the asymmetries of lesions that may have fuzzy borders. The main idea is enhancing the symmetric distant (eSD) with a number of variations. Results from experiments, which use the digitized images from the Lesion Clinic in Vancouver, Canada have shown the good discriminating power of the neural network model.

UR - https://www.scopus.com/pages/publications/84883886538

U2 - 10.1109/BIBE.2003.1188955

DO - 10.1109/BIBE.2003.1188955

M3 - Conference article published in proceeding or book

SP - 223

EP - 230

BT - Proceedings - 3rd IEEE Symposium on BioInformatics and BioEngineering, BIBE 2003

PB - IEEE

T2 - 3rd IEEE Symposium on BioInformatics and BioEngineering, BIBE 2003

Y2 - 10 March 2003 through 12 March 2003

ER -

Determining the asymmetries of skin lesions with fuzzy borders

Abstract

Conference

UN SDGs

ASJC Scopus subject areas

More information

Other files and links

Fingerprint

Cite this