Literature DB >> 12709133

Colour histogram analysis for melanoma discrimination in clinical images.

Yunus Faziloglu1, R Joe Stanley, Randy H Moss, William Van Stoecker, Rob P McLean.   

Abstract

BACKGROUND: Malignant melanoma, the most deadly form of skin cancer, has a good prognosis if treated in the curable early stages. Colour provides critical discriminating information for the diagnosis of malignant melanoma.
METHODS: This research introduces a three-dimensional relative colour histogram analysis technique to identify colours characteristic of melanomas and then applies these 'melanoma colours' to differentiate benign skin lesions from melanomas. The relative colour of a skin lesion is determined based on subtracting a representative colour of the surrounding skin from each lesion pixel. A colour mapping for 'melanoma colours' is determined using a training set of images. A percent melanoma colour feature, defined as the percentage of the lesion pixels that are melanoma colours, is used for discriminating melanomas from benign lesions. The technique is evaluated using a clinical image data set of 129 malignant melanomas and 129 benign lesions consisting of 40 seborrheic keratoses and 89 nevocellular nevi.
RESULTS: Using the percent melanoma colour feature for discrimination, experimental results yield correct melanoma and benign lesion discrimination rates of 84.3 and 83.0%, respectively.
CONCLUSIONS: The results presented in this work suggest that lesion colour in clinical images is strongly related to the presence of melanoma in that lesion. However, colour information should be combined with other information in order to further reduce the false negative and false positive rates.

Entities:  

Mesh:

Year:  2003        PMID: 12709133      PMCID: PMC3191539          DOI: 10.1034/j.1600-0846.2003.00030.x

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


  19 in total

1.  Accuracy in the clinical diagnosis of malignant melanoma.

Authors:  C M Grin; A W Kopf; B Welkovich; R S Bart; M J Levenstein
Journal:  Arch Dermatol       Date:  1990-06

2.  Shape analysis for classification of malignant melanoma.

Authors:  E Claridge; P N Hall; M Keefe; J P Allen
Journal:  J Biomed Eng       Date:  1992-05

3.  Computerized system to enhance the clinical diagnosis of pigmented cutaneous malignancies.

Authors:  M Landau; H Matz; E Tur; M Dvir; S Brenner
Journal:  Int J Dermatol       Date:  1999-06       Impact factor: 2.736

4.  Computerized evaluation of pigmented skin lesion images recorded by a videomicroscope: comparison between polarizing mode observation and oil/slide mode observation.

Authors:  S Seidenari; M Burroni; G Dell'Eva; P Pepe; B Belletti
Journal:  Skin Res Technol       Date:  1995-11       Impact factor: 2.365

Review 5.  An expert system for the early detection of melanoma using knowledge-based image analysis.

Authors:  A P Dhawan
Journal:  Anal Quant Cytol Histol       Date:  1988-12       Impact factor: 0.302

6.  Diagnostic accuracy in malignant melanoma.

Authors:  A W Kopf; M Mintzis; R S Bart
Journal:  Arch Dermatol       Date:  1975-10

7.  Automatic detection of irregular borders in melanoma and other skin tumors.

Authors:  J E Golston; W V Stoecker; R H Moss; I P Dhillon
Journal:  Comput Med Imaging Graph       Date:  1992 May-Jun       Impact factor: 4.790

8.  Automatic detection of asymmetry in skin tumors.

Authors:  W V Stoecker; W W Li; R H Moss
Journal:  Comput Med Imaging Graph       Date:  1992 May-Jun       Impact factor: 4.790

9.  Skin cancer recognition by computer vision.

Authors:  R H Moss; W V Stoecker; S J Lin; S Muruganandhan; K F Chu; K M Poneleit; C D Mitchell
Journal:  Comput Med Imaging Graph       Date:  1989 Jan-Feb       Impact factor: 4.790

10.  Automatic color segmentation of images with application to detection of variegated coloring in skin tumors.

Authors:  S E Umbaugh; R H Moss; W V Stoecker
Journal:  IEEE Eng Med Biol Mag       Date:  1989
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  5 in total

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

Authors:  R Joe Stanley; William V Stoecker; Randy H Moss
Journal:  Skin Res Technol       Date:  2007-02       Impact factor: 2.365

2.  A systematic heuristic approach for feature selection for melanoma discrimination using clinical images.

Authors:  Ying Chang; R Joe Stanley; Randy H Moss; William Van Stoecker
Journal:  Skin Res Technol       Date:  2005-08       Impact factor: 2.365

3.  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

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

Authors:  Recep Erol; Mustafa Bayraktar; Sinan Kockara; Sertan Kaya; Tansel Halic
Journal:  BMC Bioinformatics       Date:  2017-12-28       Impact factor: 3.169

5.  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.

Authors:  Yoshitaka Kubota; Nobuyuki Mitsukawa; Kumiko Chuma; Shinsuke Akita; Yoshitaro Sasahara; Naoaki Rikihisa; Kaneshige Satoh
Journal:  Burns Trauma       Date:  2016-05-05
  5 in total

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