Literature DB >> 1823631

Computer image analysis of pigmented skin lesions.

A Green1, N Martin, G McKenzie, J Pfitzner, F Quintarelli, B W Thomas, M O'Rourke, N Knight.   

Abstract

To assist in the distinction of melanoma from benign pigmented lesions, an imaging system was developed, comprising a frame grabber, a microcomputer, a colour video camera and flash lighting with red, green and infrared filters. Over an 18-month period, video images of 70 unselected pigmented lesions for which complete diagnostic data were available, were successfully captured using the camera. Analysis software extracted features relevant to the size, colour, shape and boundary of each lesion, and these features were correlated with clinical and histological characteristics on which standard diagnoses of skin tumours are based. For discriminant analysis based on image analysis measurements, equal probabilities were assigned to three specified diagnostic groups, namely melanoma, naevi and 'other', and four of five melanomas were correctly classified when infrared data were included. However when infrared measurements were omitted, all five melanomas were correctly classified, and the overall accuracy of classification of pigmented lesions was 71%. This system holds promise as an aid in the clinical distinction of melanoma from benign pigmented skin lesions.

Entities:  

Mesh:

Year:  1991        PMID: 1823631     DOI: 10.1097/00008390-199111000-00002

Source DB:  PubMed          Journal:  Melanoma Res        ISSN: 0960-8931            Impact factor:   3.599


  9 in total

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Review 2.  Melanoma Early Detection: Big Data, Bigger Picture.

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Review 3.  Current and emerging technologies in melanoma diagnosis: the state of the art.

Authors:  Estee L Psaty; Allan C Halpern
Journal:  Clin Dermatol       Date:  2009 Jan-Feb       Impact factor: 3.541

4.  Aid to diagnosis of melanoma in primary medical care.

Authors:  C B Del Mar; A C Green
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5.  Skin cancer recognition by using a neuro-fuzzy system.

Authors:  Bareqa Salah; Mohammad Alshraideh; Rasha Beidas; Ferial Hayajneh
Journal:  Cancer Inform       Date:  2011-02-02

6.  Visual inspection and dermoscopy, alone or in combination, for diagnosing keratinocyte skin cancers in adults.

Authors:  Jacqueline Dinnes; Jonathan J Deeks; Naomi Chuchu; Rubeta N Matin; Kai Yuen Wong; Roger Benjamin Aldridge; Alana Durack; Abha Gulati; Sue Ann Chan; Louise Johnston; Susan E Bayliss; Jo Leonardi-Bee; Yemisi Takwoingi; Clare Davenport; Colette O'Sullivan; Hamid Tehrani; Hywel C Williams
Journal:  Cochrane Database Syst Rev       Date:  2018-12-04

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

Authors:  Lavinia Ferrante di Ruffano; Yemisi Takwoingi; Jacqueline Dinnes; Naomi Chuchu; Susan E Bayliss; Clare Davenport; Rubeta N Matin; Kathie Godfrey; Colette O'Sullivan; Abha Gulati; Sue Ann Chan; Alana Durack; Susan O'Connell; Matthew D Gardiner; Jeffrey Bamber; Jonathan J Deeks; Hywel C Williams
Journal:  Cochrane Database Syst Rev       Date:  2018-12-04

8.  Visual inspection for diagnosing cutaneous melanoma in adults.

Authors:  Jacqueline Dinnes; Jonathan J Deeks; Matthew J Grainge; Naomi Chuchu; Lavinia Ferrante di Ruffano; Rubeta N Matin; David R Thomson; Kai Yuen Wong; Roger Benjamin Aldridge; Rachel Abbott; Monica Fawzy; Susan E Bayliss; Yemisi Takwoingi; Clare Davenport; Kathie Godfrey; Fiona M Walter; Hywel C Williams
Journal:  Cochrane Database Syst Rev       Date:  2018-12-04

9.  Comparability of naevus counts between and within examiners, and comparison with computer image analysis.

Authors:  J F Aitken; A Green; A Eldridge; L Green; J Pfitzner; D Battistutta; N G Martin
Journal:  Br J Cancer       Date:  1994-03       Impact factor: 7.640

  9 in total

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