Literature DB >> 14757921

A system for the acquisition of reproducible digital skin lesions images.

Ilias Maglogiannis1, Dimitrios I Kosmopoulos.   

Abstract

A major issue concerning the design and implementation of an image acquisition system for skin lesions is its ability to capture reproducible images. The reproducibility is considered essential for image analysis and for the comparison of sequential images during follow-up studies. This paper describes a prototype image acquisition system that includes a standardized illumination and capturing geometry with polarizing filters and a series of software corrections: Calibration to Black, White and Color for color constancy, Internal camera Parameters adjustment and Pose extraction for stereo vision, Shading correction and Noise Filtering for color quality. The validity of the calibration procedure and the images' reproducibility were tested by capturing sample images in three different lighting conditions: dark, medium and intense lighting. For each case the average values of the three color planes RGB and their standard deviations were calculated; the measured error differences ranged between 0.7 and 12.9 (in the 0-255 scale). Preliminary experiments for stereo measurements provided repeatability of about 0.3 mm. The above results demonstrate the reproducibility of the captured images at a satisfactory level. The developed prototype was also evaluated clinically, for its ability to support the construction of knowledge-based decision systems and for telemedicine, thus to support telemedical sessions in dermatology.

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Mesh:

Year:  2003        PMID: 14757921

Source DB:  PubMed          Journal:  Technol Health Care        ISSN: 0928-7329            Impact factor:   1.285


  2 in total

1.  Automatic colorimetric calibration of human wounds.

Authors:  Sven Van Poucke; Yves Vander Haeghen; Kris Vissers; Theo Meert; Philippe Jorens
Journal:  BMC Med Imaging       Date:  2010-03-18       Impact factor: 1.930

2.  Characterization of digital medical images utilizing support vector machines.

Authors:  Ilias G Maglogiannis; Elias P Zafiropoulos
Journal:  BMC Med Inform Decis Mak       Date:  2004-03-10       Impact factor: 2.796

  2 in total

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