Literature DB >> 16221140

Practical color calibration for dermoscopy, applied to a digital epiluminescence microscope.

C Grana1, G Pellacani, S Seidenari.   

Abstract

BACKGROUND/
PURPOSE: The assessment of colors is essential for melanoma (MM) diagnosis, both for pattern analysis on dermoscopic images, and when using semiquantitative methods. Our aim was to provide a simple, precise characterization and reproducible calibration of the color response for dermoscopic instruments.
METHODS: Three processes were used to correct the non-uniform illumination pattern of the instrument, to easily estimate the camera gamma settings and to describe the color space conversion matrices required to produce standard images, in any color space. A specific color space was also developed to optimize the representation of dermatoscopic colors. The calibration technique was tested both on synthetic reference surfaces and on real images by comparing the difference between the images colors obtained with two different equipments.
RESULTS: The differences between the images acquired by means of the two instruments, calculated on the reference patterns after calibration, were up to 10 times lower then before, while comparison of histograms referring to real images provided an improvement of about seven times on average.
CONCLUSIONS: A complete workflow for dermatologic image calibration, which allows the user to continue using his own software and algorithms, but with a much higher informative content, is presented. The technique is simple and may improve cooperation between different research centers, in teleconsulting contexts or for result comparisons.

Entities:  

Mesh:

Year:  2005        PMID: 16221140     DOI: 10.1111/j.0909-725X.2005.00127.x

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


  2 in total

1.  Applying a decision support system in clinical practice: results from melanoma diagnosis.

Authors:  Stephan Dreiseitl; Michael Binder; Staal Vinterbo; Harald Kittler
Journal:  AMIA Annu Symp Proc       Date:  2007-10-11

Review 2.  Computer vision for microscopy diagnosis of malaria.

Authors:  F Boray Tek; Andrew G Dempster; Izzet Kale
Journal:  Malar J       Date:  2009-07-13       Impact factor: 2.979

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.