Literature DB >> 3819073

A possible new tool for clinical diagnosis of melanoma: the computer.

N Cascinelli, M Ferrario, T Tonelli, E Leo.   

Abstract

The analysis of cutaneous melanoma images by two coupled computers (IBM 7350/4361) was carried out on twenty color slides. Each color slide was digitized with a spatial reduction of 25 X 25 microns. Classic technics of digital image analysis and new algorithms were used to improve the contrast on the full image or a portion of it, contrast a skin lesion with statistical information deduced from another lesion, evaluate the shape of the lesion, the roughness of the surface, and the transition region from the lesion to the normal skin, and analyze a lesion from the chromatic point of view. The theoretical reasons of interest are to have an objective method that is easy to standardize and reliably repeatable and to be able to analyze details not perceivable by the human eye. If the same technic are used in the evaluation of histologic characteristics of the lesions, a chance of making much more sophisticated clinicopathologic correlations will be available. The system needs to be improved at the technical level so that the response time of acquisition of the digitized images is shortened by the use of a digital television camera and the development of new computer programs to be run on a small computer. Evaluation of the system's sensitivity and specificity and an adequate clinical trial are needed.

Entities:  

Mesh:

Year:  1987        PMID: 3819073     DOI: 10.1016/s0190-9622(87)70050-4

Source DB:  PubMed          Journal:  J Am Acad Dermatol        ISSN: 0190-9622            Impact factor:   11.527


  12 in total

1.  A methodological approach to the classification of dermoscopy images.

Authors:  M Emre Celebi; Hassan A Kingravi; Bakhtiyar Uddin; Hitoshi Iyatomi; Y Alp Aslandogan; William V Stoecker; Randy H Moss
Journal:  Comput Med Imaging Graph       Date:  2007-03-26       Impact factor: 4.790

2.  A physician's workstation designed for NASA and earth-based applications.

Authors:  R R Grams; F S Yu; E Iddings; R Fiorentino
Journal:  J Med Syst       Date:  1992-02       Impact factor: 4.460

3.  Mitotic rate in melanoma: prognostic value of immunostaining and computer-assisted image analysis.

Authors:  Christopher S Hale; Meng Qian; Michelle W Ma; Patrick Scanlon; Russell S Berman; Richard L Shapiro; Anna C Pavlick; Yongzhao Shao; David Polsky; Iman Osman; Farbod Darvishian
Journal:  Am J Surg Pathol       Date:  2013-06       Impact factor: 6.394

4.  Melanoma Detection Using Spatial and Spectral Analysis on Superpixel Graphs.

Authors:  Mahmoud H Annaby; Asmaa M Elwer; Muhammad A Rushdi; Mohamed E M Rasmy
Journal:  J Digit Imaging       Date:  2021-01-07       Impact factor: 4.056

5.  Hyperspectral imaging in automated digital dermoscopy screening for melanoma.

Authors:  Anna-Marie Hosking; Brandon J Coakley; Dorothy Chang; Faezeh Talebi-Liasi; Samantha Lish; Sung Won Lee; Amanda M Zong; Ian Moore; James Browning; Steven L Jacques; James G Krueger; Kristen M Kelly; Kenneth G Linden; Daniel S Gareau
Journal:  Lasers Surg Med       Date:  2019-01-17       Impact factor: 4.025

6.  A machine learning approach to automatic detection of irregularity in skin lesion border using dermoscopic images.

Authors:  Abder-Rahman Ali; Jingpeng Li; Guang Yang; Sally Jane O'Shea
Journal:  PeerJ Comput Sci       Date:  2020-06-29

7.  Lacunarity analysis: a promising method for the automated assessment of melanocytic naevi and melanoma.

Authors:  Stephen Gilmore; Rainer Hofmann-Wellenhof; Jim Muir; H Peter Soyer
Journal:  PLoS One       Date:  2009-10-13       Impact factor: 3.240

Review 8.  Computer aided diagnostic support system for skin cancer: a review of techniques and algorithms.

Authors:  Ammara Masood; Adel Ali Al-Jumaily
Journal:  Int J Biomed Imaging       Date:  2013-12-23

9.  A Novel Fuzzy Multilayer Perceptron (F-MLP) for the Detection of Irregularity in Skin Lesion Border Using Dermoscopic Images.

Authors:  Abder-Rahman Ali; Jingpeng Li; Summrina Kanwal; Guang Yang; Amir Hussain; Sally Jane O'Shea
Journal:  Front Med (Lausanne)       Date:  2020-07-07

Review 10.  What is AI? Applications of artificial intelligence to dermatology.

Authors:  X Du-Harpur; F M Watt; N M Luscombe; M D Lynch
Journal:  Br J Dermatol       Date:  2020-03-29       Impact factor: 9.302

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.