Abstract
In this study, we propose a smart transcription algorithm for translation and/or rotation motions. This algorithm has two phases: calculating the differences between real and virtual 2D depth images, and searching the motion space defined by three translation and three rotation degrees of freedom based on the depth differences. One depth image is captured for a real liver using a Kinect v2 depth camera and another depth image is obtained for a virtual liver (a polyhedron in stereo-lithography (STL) format by z-buffering with a graphics processing unit). The STL data are converted from Digital Imaging and Communication in Medicine (DICOM) data, where the DICOM data are captured from a patient’s liver using magnetic resonance imaging and/or a computed tomography scanner. In this study, we evaluated the motion precision of our proposed algorithm based on several experiments based using a Kinect v2 depth camera.
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Acknowledgments
This study was supported partly by 2014 Grants-in-Aid for Scientific Research (No. 26289069) from the Ministry of Education, Culture, Sports, Science, and Technology, Japan. Further support was provided by the 2014 Cooperation Research Fund from the Graduate School at Osaka Electro-Communication University.
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Noborio, H. et al. (2016). Tracking a Real Liver Using a Virtual Liver and an Experimental Evaluation with Kinect v2. In: Ortuño, F., Rojas, I. (eds) Bioinformatics and Biomedical Engineering. IWBBIO 2016. Lecture Notes in Computer Science(), vol 9656. Springer, Cham. https://doi.org/10.1007/978-3-319-31744-1_14
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DOI: https://doi.org/10.1007/978-3-319-31744-1_14
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