Literature DB >> 18486019

Digital image analysis for diagnosis of skin tumors.

Andreas Blum1, Iris Zalaudek, Giuseppe Argenziano.   

Abstract

Between 1987 and 2007, different groups developed digital image analysis systems for the diagnosis of benign and malignant skin tumors. As the result of significant differences in the technical devices, the number, the nature and benign/malignant ratio of included skin tumors, different variables and statistical methods any comparison of these different systems and their results is difficult. For the use and comparison of the diagnostic performance of different digital image analysis systems in the future, some principle basic conditions are required: All used systems should have a standardized recording system and calibration. First, melanocytic and nonmelanocytic lesions should be included for the development of the diagnostic algorithms. Critical analyses of the results should answer the question if in future only melanocytic lesions should be analyzed or all pigmented and nonpigmented lesions. This will also lead to the answer if only dermatologists or all specialities of medical doctors will use such a system. All artifacts (eg, hairs, air bubbles) should be removed. The number of variables should be chosen according to the number of included melanomas. A high number of benign skin lesions should be included. Of all lesions only 10% or better less should be invasive melanomas. Each system should be developed by a training-set and controlled by an independent test-set. Each system should be controlled by the user with the final decision and responsibility and tested by independent users without any conflict of financial interest.

Entities:  

Mesh:

Year:  2008        PMID: 18486019     DOI: 10.1016/j.sder.2007.12.005

Source DB:  PubMed          Journal:  Semin Cutan Med Surg        ISSN: 1085-5629


  4 in total

1.  Histology image analysis for carcinoma detection and grading.

Authors:  Lei He; L Rodney Long; Sameer Antani; George R Thoma
Journal:  Comput Methods Programs Biomed       Date:  2012-03-20       Impact factor: 5.428

2.  Computer-Aided Decision Support for Melanoma Detection Applied on Melanocytic and Nonmelanocytic Skin Lesions: A Comparison of Two Systems Based on Automatic Analysis of Dermoscopic Images.

Authors:  Kajsa Møllersen; Herbert Kirchesch; Maciel Zortea; Thomas R Schopf; Kristian Hindberg; Fred Godtliebsen
Journal:  Biomed Res Int       Date:  2015-11-26       Impact factor: 3.411

3.  Computer-aided diagnosis of skin lesions using conventional digital photography: a reliability and feasibility study.

Authors:  Wen-Yu Chang; Adam Huang; Chung-Yi Yang; Chien-Hung Lee; Yin-Chun Chen; Tian-Yau Wu; Gwo-Shing Chen
Journal:  PLoS One       Date:  2013-11-04       Impact factor: 3.240

Review 4.  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
  4 in total

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