Literature DB >> 17250534

A relative color approach to color discrimination for malignant melanoma detection in dermoscopy images.

R Joe Stanley1, William V Stoecker, Randy H Moss.   

Abstract

BACKGROUND: Skin lesion color is an important feature for diagnosing malignant melanoma. In previous research, skin lesion color was investigated for discriminating malignant melanoma lesions from benign lesions in clinical images. Colors characteristics of melanoma were determined using color histogram analysis over a training set of images. Percent melanoma color and color clustering ratio features were used to quantify the presence of melanoma-colored pixels within skin lesions for skin lesion discrimination.
METHODS: In this research, the relative color histogram analysis technique is used to evaluate skin lesion discrimination based on color feature calculations in different regions of the skin lesion in dermoscopy images. The histogram analysis technique is examined for varying training set sizes from the set of 113 malignant melanomas and 113 benign dysplastic nevi images.
RESULTS: Experimental results show improved discrimination capability for feature calculations focused in the interior lesion region. Recognition rates for malignant melanoma and dysplastic nevi as high as 87.7% and 74.9%, respectively, are observed for the color clustering ratio computed using the outer 75% uniformly distributed area with a 10% offset within the boundary.
CONCLUSIONS: Experimental results appear to indicate that the melanoma color feature information is located in the interior of the lesion, excluding the 10% central-most region. The techniques presented here including the use of relative color and the determination of benign and malignant regions of the relative color histogram may be applicable to any set of images of benign and malignant lesions.

Entities:  

Mesh:

Year:  2007        PMID: 17250534      PMCID: PMC3184887          DOI: 10.1111/j.1600-0846.2007.00192.x

Source DB:  PubMed          Journal:  Skin Res Technol        ISSN: 0909-752X            Impact factor:   2.365


  19 in total

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2.  Techniques for a structural analysis of dermatoscopic imagery.

Authors:  M G Fleming; C Steger; J Zhang; J Gao; A B Cognetta; I Pollak; C R Dyer
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4.  Automatic differentiation of melanoma from melanocytic nevi with multispectral digital dermoscopy: a feasibility study.

Authors:  M Elbaum; A W Kopf; H S Rabinovitz; R G Langley; H Kamino; M C Mihm; A J Sober; G L Peck; A Bogdan; D Gutkowicz-Krusin; M Greenebaum; S Keem; M Oliviero; S Wang
Journal:  J Am Acad Dermatol       Date:  2001-02       Impact factor: 11.527

5.  Computer image analysis in the diagnosis of melanoma.

Authors:  A Green; N Martin; J Pfitzner; M O'Rourke; N Knight
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6.  Epiluminescence microscopy for the diagnosis of doubtful melanocytic skin lesions. Comparison of the ABCD rule of dermatoscopy and a new 7-point checklist based on pattern analysis.

Authors:  G Argenziano; G Fabbrocini; P Carli; V De Giorgi; E Sammarco; M Delfino
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7.  Early detection of malignant melanoma: the role of physician examination and self-examination of the skin.

Authors:  R J Friedman; D S Rigel; A W Kopf
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9.  Neural network diagnosis of malignant melanoma from color images.

Authors:  F Ercal; A Chawla; W V Stoecker; H C Lee; R H Moss
Journal:  IEEE Trans Biomed Eng       Date:  1994-09       Impact factor: 4.538

10.  Colour histogram analysis for melanoma discrimination in clinical images.

Authors:  Yunus Faziloglu; R Joe Stanley; Randy H Moss; William Van Stoecker; Rob P McLean
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  12 in total

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2.  Real-time supervised detection of pink areas in dermoscopic images of melanoma: importance of color shades, texture and location.

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4.  A basis function feature-based approach for skin lesion discrimination in dermatology dermoscopy images.

Authors:  R Joe Stanley; William V Stoecker; Randy H Moss; Harold S Rabinovitz; Armand B Cognetta; Giuseppe Argenziano; H Peter Soyer
Journal:  Skin Res Technol       Date:  2008-11       Impact factor: 2.365

5.  The Role of Color and Morphologic Characteristics in Dermoscopic Diagnosis.

Authors:  Shirin Bajaj; Michael A Marchetti; Cristian Navarrete-Dechent; Stephen W Dusza; Kivanc Kose; Ashfaq A Marghoob
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6.  Assisting Main Task Learning by Heterogeneous Auxiliary Tasks with Applications to Skin Cancer Screening.

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7.  Computer-assisted diagnosis techniques (dermoscopy and spectroscopy-based) for diagnosing skin cancer in adults.

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8.  Texture based skin lesion abruptness quantification to detect malignancy.

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Review 9.  Computer aided diagnostic support system for skin cancer: a review of techniques and algorithms.

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10.  Hyperpigmentation after surgery for a deep dermal burn of the dorsum of the hand: partial-thickness debridement followed by medium split-thickness skin grafting vs full-thickness debridement followed by thick split-thickness skin grafting.

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