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Coarse-to-fine localization of anatomical landmarks in CT images based on multi-scale local appearance and rotation-invariant spatial landmark distribution model.

M. Nemoto, Y. Masutani, S. Hanaoka, Y. Nomura, S. Miki, T. Yoshikawa, N. Hayashi, and K. Ohtomo. Medical Imaging: Image Processing, volume 8669 of SPIE Proceedings, page 866917. SPIE, (2013)

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Miki Tsukada

ivko Miki

Nicole Mikisch

Masayuki Miki

Isao Miki

Other publications of authors with the same name

HoTPiG: a novel graph-based 3-D image feature set and its applications to computer-assisted detection of cerebral aneurysms and lung nodules.S. Hanaoka, Y. Nomura, T. Takenaga, M. Murata, T. Nakao, S. Miki, T. Yoshikawa, N. Hayashi, O. Abe, and A. Shimizu. Int. J. Comput. Assist. Radiol. Surg., 14 (12): 2095-2107 (2019)Preliminary study of generalized semiautomatic segmentation for 3D voxel labeling of lesions based on deep learning.Y. Nomura, S. Hanaoka, T. Takenaga, T. Nakao, H. Shibata, S. Miki, T. Yoshikawa, T. Watadani, N. Hayashi, and O. Abe. Int. J. Comput. Assist. Radiol. Surg., 16 (11): 1901-1913 (2021)Automatic detection of over 100 anatomical landmarks in medical CT images: A framework with independent detectors and combinatorial optimization.S. Hanaoka, A. Shimizu, M. Nemoto, Y. Nomura, S. Miki, T. Yoshikawa, N. Hayashi, K. Ohtomo, and Y. Masutani. Medical Image Anal., (2017)AIWolfDial 2023: Summary of Natural Language Division of 5th International AIWolf Contest.Y. Kano, N. Watanabe, K. Kagaminuma, C. Aranha, J. Lee, B. Hauer, H. Shibata, S. Miki, Y. Nakamura, T. Okubo and 16 other author(s). INLG (Generation Challenges), page 84-100. Association for Computational Linguistics, (2023)Managing Computer-Assisted Detection System Based on Transfer Learning with Negative Transfer Inhibition.I. Sato, Y. Nomura, S. Hanaoka, S. Miki, N. Hayashi, O. Abe, and Y. Masutani. KDD, page 695-704. ACM, (2018)A primitive study of voxel feature generation by multiple stacked denoising autoencoders for detecting cerebral aneurysms on MRA.M. Nemoto, N. Hayashi, S. Hanaoka, Y. Nomura, S. Miki, T. Yoshikawa, and K. Ohtomo. Medical Imaging: Computer-Aided Diagnosis, volume 9785 of SPIE Proceedings, page 97852S. SPIE, (2016)Development of training environment for deep learning with medical images on supercomputer system based on asynchronous parallel Bayesian optimization.Y. Nomura, I. Sato, T. Hanawa, S. Hanaoka, T. Nakao, T. Takenaga, T. Hoshino, Y. Sekiya, S. Miki, T. Yoshikawa and 2 other author(s). J. Supercomput., 76 (9): 7315-7332 (2020)Automatic detection of vertebral number abnormalities in body CT images.S. Hanaoka, Y. Nakano, M. Nemoto, Y. Nomura, T. Takenaga, S. Miki, T. Yoshikawa, N. Hayashi, Y. Masutani, and A. Shimizu. Int. J. Comput. Assist. Radiol. Surg., 12 (5): 719-732 (2017)Landmark-guided diffeomorphic demons algorithm and its application to automatic segmentation of the whole spine and pelvis in CT images.S. Hanaoka, Y. Masutani, M. Nemoto, Y. Nomura, S. Miki, T. Yoshikawa, N. Hayashi, K. Ohtomo, and A. Shimizu. Int. J. Comput. Assist. Radiol. Surg., 12 (3): 413-430 (2017)HoTPiG: A Novel Geometrical Feature for Vessel Morphometry and Its Application to Cerebral Aneurysm Detection.S. Hanaoka, Y. Nomura, M. Nemoto, S. Miki, T. Yoshikawa, N. Hayashi, K. Ohtomo, Y. Masutani, and A. Shimizu. MICCAI (2), volume 9350 of Lecture Notes in Computer Science, page 103-110. Springer, (2015)

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Disambiguation of "Miki, Soichiro"