Literature DB >> 18002707

3D modeling from uncalibrated color images for a complete wound assessment tool.

B Albouy1, Y Lucas, S Treuillet.   

Abstract

This paper is concerned with the 3D modeling of skin wound using uncalibrated vision techniques for the volumetric assessment of the healing process. We have developed an original approach for matching two color images captured with a free-handled digital camera and generate a semi-dense 3D model. We evaluate the precision of the inferred 3D model by registration to a ground truth on artificial wounds. The method is then applied to volumetric measurements. The clinician requirements of a global 5% precision are overshot as 3% is obtained locally. The best configuration for taking photos lies between 1.2 and 1.5 for distance ratios and between 15 degrees and 30 degrees for vergence of the stereo pair. This work is part of the ESCALE project dedicated to the design of a complete 3D and color wound assessment tool using a simple free handled digital camera: a smart solution for massive diffusion in care centers as such very low cost system should be operated directly by nurses.

Mesh:

Year:  2007        PMID: 18002707     DOI: 10.1109/IEMBS.2007.4353041

Source DB:  PubMed          Journal:  Annu Int Conf IEEE Eng Med Biol Soc        ISSN: 2375-7477


  3 in total

Review 1.  Methods to assess area and volume of wounds - a systematic review.

Authors:  Line Bisgaard Jørgensen; Jens A Sørensen; Gregor Be Jemec; Knud B Yderstraede
Journal:  Int Wound J       Date:  2015-08-06       Impact factor: 3.315

Review 2.  Diagnostic and Prognostic Utility of Non-Invasive Multimodal Imaging in Chronic Wound Monitoring: a Systematic Review.

Authors:  Rashmi Mukherjee; Suman Tewary; Aurobinda Routray
Journal:  J Med Syst       Date:  2017-02-13       Impact factor: 4.460

3.  Design and evaluation of an imager for assessing wound inflammatory responses and bioburden in a pig model.

Authors:  Ashley Dacy; Nowmi Haider; Kathryn Davis; Wenjing Hu; Liping Tang
Journal:  J Biomed Opt       Date:  2019-09       Impact factor: 3.170

  3 in total

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