Rapid pedobarographic image registration based on contour curvature and optimization |
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| Authors: | Francisco P.M. Oliveira João Manuel R.S. Tavares Todd C. Pataky |
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| Affiliation: | 1. Faculdade de Engenharia da Universidade do Porto, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal;2. Departamento de Engenharia Mecânica, Faculdade de Engenharia da Universidade do Porto, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal;3. HACB, School of Biomedical Sciences, University of Liverpool, Sherrington Buildings, Ashton Street, Liverpool, L69 3GE, UK;1. Department of Life Science and Graduate School of Life Science, Rikkyo (St. Paul’s ) University, Toshima-ku, Tokyo 171-8501, Japan;2. Application Laboratory, Rigaku Corporation, 3-9-12 Matsubara-cho, Akishima-shi, Tokyo 196-8666, Japan;3. Research Reactor Institute, Kyoto University, Kumatori, Osaka 590-0494, Japan;1. Meme Media Laboratory, Hokkaido University, Japan;2. Yukawa Institute for Theoretical Physics, Kyoto University, Japan;1. Graduate School of Energy Science, Kyoto University, Yoshida Honmachi, Sakyo-ku, Kyoto 606-8501, Japan;2. Research Institute for Sustainable Humanosphere (RISH), Kyoto University, Gokasho, Uji, Kyoto 611-0011, Japan;3. Institute of Advanced Energy (IAE), Kyoto University, Japan;1. Department of Advanced Biomedical Sciences, Pathology Section, University of Naples Federico II, Naples, Italy;2. Department of Dermatology, University of Naples Federico II, Naples, Italy;1. Epiluminescence Microscopy Unit, Istituto Dermopatico dell''Immacolata-IRCCS, Rome, Italy;2. I Dermatologic Unit, Istituto Dermopatico dell''Immacolata-IRCCS, Rome, Italy;3. Histopathology Unit, Istituto Dermopatico dell''Immacolata-IRCCS, Rome, Italy;1. Department of Ophthalmology, Morsani College of Medicine, Tampa, Florida;2. Department of Pathology and Cell Biology, Morsani College of Medicine, Tampa, Florida |
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| Abstract: | Image registration, the process of optimally aligning homologous structures in multiple images, has recently been demonstrated to support automated pixel-level analysis of pedobarographic images and, subsequently, to extract unique and biomechanically relevant information from plantar pressure data. Recent registration methods have focused on robustness, with slow but globally powerful algorithms. In this paper, we present an alternative registration approach that affords both speed and accuracy, with the goal of making pedobarographic image registration more practical for near-real-time laboratory and clinical applications. The current algorithm first extracts centroid-based curvature trajectories from pressure image contours, and then optimally matches these curvature profiles using optimization based on dynamic programming. Special cases of disconnected images (that occur in high-arched subjects, for example) are dealt with by introducing an artificial spatially linear bridge between adjacent image clusters. Two registration algorithms were developed: a ‘geometric’ algorithm, which exclusively matched geometry, and a ‘hybrid’ algorithm, which performed subsequent pseudo-optimization. After testing the two algorithms on 30 control image pairs considered in a previous study, we found that, when compared with previously published results, the hybrid algorithm improved overlap ratio (p=0.010), but both current algorithms had slightly higher mean-squared error, assumedly because they did not consider pixel intensity. Nonetheless, both algorithms greatly improved the computational efficiency (25±8 and 53±9 ms per image pair for geometric and hybrid registrations, respectively). These results imply that registration-based pixel-level pressure image analyses can, eventually, be implemented for practical clinical purposes. |
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