Authors:
Yanexis Toledo
1
;
Leandro A. F. Fernandes
1
;
Silena Herold-Garcia
2
and
Alexis P. Quesada
3
Affiliations:
1
Instituto de Computação, Universidade Federal Fluminense, Niterói, Brazil
;
2
Facultad de Matemática y Computación, Universidad de Oriente, Santiago de Cuba, Cuba
;
3
Hospital General Dr. Juan Bruno Zayas Alfonso, Santiago de Cuba, Cuba
Keyword(s):
Semantic Segmentation, Uncontrolled Viewpoint, Epipolar Constraints, Image Registration.
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 b
etween images of the same patient at different healing stages.
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