Classification of melanoma using tree structured wavelet transforms

Sachin V. Patwardhan; Atam P. Dhawan; Patricia A. Relue

doi:10.1016/S0169-2607(02)00147-5

Classification of melanoma using tree structured wavelet transforms

Sachin V. Patwardhan, Atam P. Dhawan, Patricia A. Relue

Research output: Contribution to journal › Article › peer-review

69 Scopus citations

Abstract

This paper presents a wavelet transform based tree structure model developed and evaluated for the classification of skin lesion images into melanoma and dysplastic nevus. The tree structure model utilizes a semantic representation of the spatial-frequency information contained in the skin lesion images including textural information. Results show that the presented method is effective in discriminating melanoma from dysplastic nevus. The results are also compared with those obtained using another method of developing tree structures utilizing the maximum channel energy criteria with a fixed energy ratio threshold.

Original language	English (US)
Pages (from-to)	223-239
Number of pages	17
Journal	Computer Methods and Programs in Biomedicine
Volume	72
Issue number	3
DOIs	https://doi.org/10.1016/S0169-2607(02)00147-5
State	Published - Nov 2003

All Science Journal Classification (ASJC) codes

Software
Computer Science Applications
Health Informatics

Keywords

Dysplastic nevus
Melanoma
Nevoscope
Tree structured wavelet transform

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10.1016/S0169-2607(02)00147-5

Cite this

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title = "Classification of melanoma using tree structured wavelet transforms",

abstract = "This paper presents a wavelet transform based tree structure model developed and evaluated for the classification of skin lesion images into melanoma and dysplastic nevus. The tree structure model utilizes a semantic representation of the spatial-frequency information contained in the skin lesion images including textural information. Results show that the presented method is effective in discriminating melanoma from dysplastic nevus. The results are also compared with those obtained using another method of developing tree structures utilizing the maximum channel energy criteria with a fixed energy ratio threshold.",

keywords = "Dysplastic nevus, Melanoma, Nevoscope, Tree structured wavelet transform",

author = "Patwardhan, {Sachin V.} and Dhawan, {Atam P.} and Relue, {Patricia A.}",

note = "Funding Information: The authors would like to thank all the patients whose data was used in this study. We would also like to thank The Medical College of Ohio, Toledo and Dr Prabir Chaudhari for his contribution in the data collection. We would also like to thank the Whitaker Foundation for providing partial funding for this research under the Whitaker Foundation Research Grant RG-99-0127.",

year = "2003",

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doi = "10.1016/S0169-2607(02)00147-5",

language = "English (US)",

volume = "72",

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T1 - Classification of melanoma using tree structured wavelet transforms

AU - Patwardhan, Sachin V.

AU - Dhawan, Atam P.

AU - Relue, Patricia A.

N1 - Funding Information: The authors would like to thank all the patients whose data was used in this study. We would also like to thank The Medical College of Ohio, Toledo and Dr Prabir Chaudhari for his contribution in the data collection. We would also like to thank the Whitaker Foundation for providing partial funding for this research under the Whitaker Foundation Research Grant RG-99-0127.

PY - 2003/11

Y1 - 2003/11

N2 - This paper presents a wavelet transform based tree structure model developed and evaluated for the classification of skin lesion images into melanoma and dysplastic nevus. The tree structure model utilizes a semantic representation of the spatial-frequency information contained in the skin lesion images including textural information. Results show that the presented method is effective in discriminating melanoma from dysplastic nevus. The results are also compared with those obtained using another method of developing tree structures utilizing the maximum channel energy criteria with a fixed energy ratio threshold.

AB - This paper presents a wavelet transform based tree structure model developed and evaluated for the classification of skin lesion images into melanoma and dysplastic nevus. The tree structure model utilizes a semantic representation of the spatial-frequency information contained in the skin lesion images including textural information. Results show that the presented method is effective in discriminating melanoma from dysplastic nevus. The results are also compared with those obtained using another method of developing tree structures utilizing the maximum channel energy criteria with a fixed energy ratio threshold.

KW - Dysplastic nevus

KW - Melanoma

KW - Nevoscope

KW - Tree structured wavelet transform

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JO - Computer Methods and Programs in Biomedicine

JF - Computer Methods and Programs in Biomedicine

IS - 3

ER -

Classification of melanoma using tree structured wavelet transforms

Abstract

All Science Journal Classification (ASJC) codes

Keywords

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