Abstract
This study proposes an algorithm to artificially create brain shifts in patients’ brain DICOM images. Then, we evaluate the SIFT, AKAZE, ORB, and BRISK feature point extraction algorithms for the automatic detection of local brain shifts from a patient’s pre-and postoperative DICOM images. Accurate and automatic detection of brain shifts could contribute toward the generation of accurate brain deformation models. The evaluation results suggested that the BRISK and AKAZE algorithms are most suitable for the above purpose.
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Acknowledgment
This study was supported partly by the 2020 Grants-in-Aid for Scientific Research (No. 20K04407 and 20K12053) from the Ministry of Education, Culture, Sports, Science and Technology, Japan.
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Mori, T., Nonaka, M., Kunii, T., Koeda, M., Noborio, H. (2022). Development of an Algorithm to Artificially Create Virtual Brain Deformations for Brain DICOM. In: Kurosu, M. (eds) Human-Computer Interaction. Technological Innovation. HCII 2022. Lecture Notes in Computer Science, vol 13303. Springer, Cham. https://doi.org/10.1007/978-3-031-05409-9_30
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