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Volumetric Fibular Transfer Planning With Shape-Based Indicators in Mandibular Reconstruction., , , , , , and . IEEE J. Biomed. Health Informatics, 19 (2): 581-589 (2015)Enumerated sparse extraction of important surgical planning features for mandibular reconstruction., , , , , and . EMBC, page 5519-5522. IEEE, (2020)Volumetric surgical planning system for fibular transfer in mandibular reconstruction., , , , , , , and . EMBC, page 3367-3370. IEEE, (2013)Rapidly Developing High-quality Instruction Data and Evaluation Benchmark for Large Language Models with Minimal Human Effort: A Case Study on Japanese., , , , , , and . CoRR, (2024)BERT-based Cohesion Analysis of Japanese Texts., , and . COLING, page 1323-1333. International Committee on Computational Linguistics, (2020)Regularized Three-Dimensional Generative Adversarial Nets for Unsupervised Metal Artifact Reduction in Head and Neck CT Images., , , , , and . IEEE Access, (2020)KWJA: A Unified Japanese Analyzer Based on Foundation Models., , , , , , and . ACL (demo), page 538-548. Association for Computational Linguistics, (2023)Automated Planning With Multivariate Shape Descriptors for Fibular Transfer in Mandibular Reconstruction., , , , , , , and . IEEE Trans. Biomed. Eng., 64 (8): 1772-1785 (2017)Sparse shape model for fibular transfer planning in mandibular reconstruction., , , , , , , and . EMBC, page 2508-2511. IEEE, (2016)Three-dimensional Generative Adversarial Nets for Unsupervised Metal Artifact Reduction., , , , , and . CoRR, (2019)