Literature DB >> 25131159

Modification of a melanoma discrimination index derived from hyperspectral data: a clinical trial conducted in 2 centers between March 2011 and December 2013.

T Nagaoka1, Y Kiyohara2, H Koga3, A Nakamura1, T Saida3, T Sota1,4.   

Abstract

BACKGROUND: The morphology of pigmented skin lesions (PSLs) is predominantly a result of varying concentrations and distributions of pigmented molecules such as melanin and hemoglobin. Based on these differences and the fact that their information is contained in cutaneous spectra, a hyperspectral imager (HSI) for pigmented melanoma and a single discrimination index derived from the resultant hyperspectral data are proposed.
OBJECTIVE: To develop and evaluate a new discrimination index for melanomas, compared to the previous index.
METHODS: A HSI, which is convenient for both patients and clinicians, was newly developed and used in a clinical trial conducted in 2 centers with 80 patients with primary lesions and 17 volunteers between March 2011 and December 2013. There were 24 melanomas and 110 other PSLs. A previously proposed discrimination index was used without modifications. A new index, which emphasized the essential features of melanoma, was proposed, and its performance was examined. For each index, a threshold value was set to minimize the average value of the false positive and false negative fractions. The performances of both indices were compared.
RESULTS: The sensitivity and specificity of the old index were 75% and 97%, respectively, while those of the new index were 96% and 87%.
CONCLUSION: The new index had a higher sensitivity and adequate specificity, indicating that it is more useful than the old index.
© 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Entities:  

Keywords:  computer-assisted diagnosis; early detection of melanoma; melanoma; spectrum analysis

Mesh:

Year:  2014        PMID: 25131159     DOI: 10.1111/srt.12188

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


  5 in total

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2.  Hyperspectral and multispectral image processing for gross-level tumor detection in skin lesions: a systematic review.

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4.  Hyperspectral Image-Based Night-Time Vehicle Light Detection Using Spectral Normalization and Distance Mapper for Intelligent Headlight Control.

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5.  Differentiating Malignant from Benign Pigmented or Non-Pigmented Skin Tumours-A Pilot Study on 3D Hyperspectral Imaging of Complex Skin Surfaces and Convolutional Neural Networks.

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  5 in total

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