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<!-- views/paperById.ejs --> <!DOCTYPE html> <html> <head> <meta charset="utf-8"> <title>SCITEPRESS - SCIENCE AND TECHNOLOGY PUBLICATIONS</title> <meta name ="description" content="Digital Library" /> <meta name="citation_language" content="en"> <meta name="citation_title" content="U-Net-based DFU Tissue Segmentation and Registration on Uncontrolled Dermoscopic Images"> <meta name="citation_abstract" content="Diabetic Foot Ulcers (DFUs) are aggressive wounds with high morbimortality due to their slow healing capacity and rapid tissue degeneration, which cause complications such as infection, gangrene, and amputation. The automatic analysis of the evolution of tissues associated with DFU allows the quick identification and treatment of possible complications. In this paper, our contribution is twofold. First, we present a new DFU dataset composed of 222 images labeled by specialists. The images followed the healing process of patients of an experimental treatment and were captured under uncontrolled viewpoint and illumination conditions. To the best of our knowledge, this is the first DFU dataset whose images include the identification of background and six different classes of tissues. The second contribution is an U-Net-based segmentation and registration procedure that uses features computed by hidden layers of the network and epipolar constraints to identify pixelwise correspondences between images of the same patient at different healing stages."> <meta name="citation_publication_date" content="2022/02/06"> <meta name="citation_conference_title" content="International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP)"> <meta name="citation_keywords" content="Semantic Segmentation; Uncontrolled Viewpoint; Epipolar Constraints; Image Registration;"> <meta name="citation_doi" content="10.5220/0010868600003124"> <meta name="citation_isbn" content="978-989-758-555-5"> <meta name="citation_volume" content="2"> <meta name="citation_firstpage" content="510"> <meta name="citation_lastpage" content="517"> <meta name="citation_publisher" content="SCITEPRESS"> <meta name="citation_author" content="Yanexis Toledo" > <meta name="citation_author_institution" content="Instituto de Computa莽茫o, Universidade Federal Fluminense, Niter贸i, Brazil" > <meta name="citation_author" content="Leandro A. F. Fernandes" > <meta name="citation_author_institution" content="Instituto de Computa莽茫o, Universidade Federal Fluminense, Niter贸i, Brazil" > <meta name="citation_author" content="Silena Herold-Garcia" > <meta name="citation_author_institution" content="Facultad de Matem谩tica y Computaci贸n, Universidad de Oriente, Santiago de Cuba, Cuba" > <meta name="citation_author" content="Alexis P. Quesada" > <meta name="citation_author_institution" content="Hospital General Dr. Juan Bruno Zayas Alfonso, Santiago de Cuba, Cuba" > <meta name="citation_abstract_html_url" content="/PublishedPapers/2022/108686"> <meta name="citation_pdf_url" content="/PublishedPapers/2022/108686/108686.pdf"> </head> <body> <article> <a href="/publishedPapers/2022/108686/pdf/index.html"><h1 class="citation_title">U-Net-based DFU Tissue Segmentation and Registration on Uncontrolled Dermoscopic Images</h1></a> <h3 class="citation_author"> Yanexis Toledo, Leandro A. F. Fernandes, Silena Herold-Garcia, Alexis P. Quesada</h3> <h4 class="citation_publication_date">2022</h4> <h4>Abstract</h4> <p class="citation_abstract">Diabetic Foot Ulcers (DFUs) are aggressive wounds with high morbimortality due to their slow healing capacity and rapid tissue degeneration, which cause complications such as infection, gangrene, and amputation. The automatic analysis of the evolution of tissues associated with DFU allows the quick identification and treatment of possible complications. In this paper, our contribution is twofold. First, we present a new DFU dataset composed of 222 images labeled by specialists. The images followed the healing process of patients of an experimental treatment and were captured under uncontrolled viewpoint and illumination conditions. To the best of our knowledge, this is the first DFU dataset whose images include the identification of background and six different classes of tissues. The second contribution is an U-Net-based segmentation and registration procedure that uses features computed by hidden layers of the network and epipolar constraints to identify pixelwise correspondences between images of the same patient at different healing stages.</p> <a href="/PublishedPapers/2022/108686/108686.pdf" class="citation_pdf_url">Download</a> <br /> <br /> <br/> <h4 style="margin:0;">Paper Citation</h4> <br/> <h4 style="margin:0;">in Harvard Style</h4> <p style="margin:0;">Toledo Y., Fernandes L., Herold-Garcia S. and Quesada A. (2022). <b>U-Net-based DFU Tissue Segmentation and Registration on Uncontrolled Dermoscopic Images</b>. In <i>Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 4: VISAPP</i>; ISBN 978-989-758-555-5, SciTePress, pages 510-517. DOI: 10.5220/0010868600003124</p> <br/> <h4 style="margin:0;">in Bibtex Style</h4> <p style="margin:0;">@conference{visapp22,<br />author={Yanexis Toledo and Leandro A. F. Fernandes and Silena Herold-Garcia and Alexis P. Quesada},<br />title={U-Net-based DFU Tissue Segmentation and Registration on Uncontrolled Dermoscopic Images},<br />booktitle={Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 4: VISAPP},<br />year={2022},<br />pages={510-517},<br />publisher={SciTePress},<br />organization={INSTICC},<br />doi={10.5220/0010868600003124},<br />isbn={978-989-758-555-5},<br />}</p> <br/> <h4 style="margin:0;">in EndNote Style</h4> <p style="margin:0;">TY - CONF <br /><br />JO - Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 4: VISAPP<br />TI - U-Net-based DFU Tissue Segmentation and Registration on Uncontrolled Dermoscopic Images<br />SN - 978-989-758-555-5<br />AU - Toledo Y. <br />AU - Fernandes L. <br />AU - Herold-Garcia S. <br />AU - Quesada A. <br />PY - 2022<br />SP - 510<br />EP - 517<br />DO - 10.5220/0010868600003124<br />PB - SciTePress<br /></p> <br/> </article> </body> </html>