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Mizuho Nishio
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2020 – today
- 2024
- [j10]Mizuho Nishio, Eiji Ota:
Optimizing statistical evaluation of multiclass classification in diagnostic radiology: a study of the two-parameter multidimensional nominal response model. PeerJ Comput. Sci. 10: e2380 (2024) - [c4]Mizuho Nishio, Hidetoshi Matsuo, Takaaki Matsunaga:
Automatic Structuring of Radiology Reports of Chest X-Ray Images Using Large Language Model. COMPSAC 2024: 1952-1954 - [i9]Hidetoshi Matsuo, Mizuho Nishio, Takaaki Matsunaga, Koji Fujimoto, Takamichi Murakami:
Exploring Multilingual Large Language Models for Enhanced TNM classification of Radiology Report in lung cancer staging. CoRR abs/2406.06591 (2024) - 2023
- [j9]Mizuho Nishio, Eiji Ota, Hidetoshi Matsuo, Takaaki Matsunaga, Aki Miyazaki, Takamichi Murakami:
Comparison between pystan and numpyro in Bayesian item response theory: evaluation of agreement of estimated latent parameters and sampling performance. PeerJ Comput. Sci. 9: e1620 (2023) - [c3]Sanghwan Kim, Farhad Nooralahzadeh, Morteza Rohanian, Koji Fujimoto, Mizuho Nishio, Ryo Sakamoto, Fabio Rinaldi
, Michael Krauthammer:
Boosting Radiology Report Generation by Infusing Comparison Prior. BioNLP@ACL 2023: 50-61 - [i8]Sanghwan Kim, Farhad Nooralahzadeh, Morteza Rohanian, Koji Fujimoto, Mizuho Nishio, Ryo Sakamoto, Fabio Rinaldi, Michael Krauthammer:
Boosting Radiology Report Generation by Infusing Comparison Prior. CoRR abs/2305.04561 (2023) - [i7]Takaaki Matsunaga, Atsushi K. Kono, Hidetoshi Matsuo, Kaoru Kitagawa, Mizuho Nishio, Hiromi Hashimura, Yu Izawa, Takayoshi Toba, Kazuki Ishikawa, Akie Katsuki, Kazuyuki Ohmura, Takamichi Murakami:
Development of pericardial fat count images using a combination of three different deep-learning models. CoRR abs/2307.12316 (2023) - [i6]Amos Calamida, Farhad Nooralahzadeh, Morteza Rohanian, Koji Fujimoto, Mizuho Nishio, Michael Krauthammer
Radiology-Aware Model-Based Evaluation Metric for Report Generation. CoRR abs/2311.16764 (2023) - 2021
- [j8]Mizuho Nishio, Koji Fujimoto
Lung Cancer Segmentation With Transfer Learning: Usefulness of a Pretrained Model Constructed From an Artificial Dataset Generated Using a Generative Adversarial Network. Frontiers Artif. Intell. 4: 694815 (2021) - [j7]Mizuho Nishio
Lung segmentation on chest X-ray images in patients with severe abnormal findings using deep learning. Int. J. Imaging Syst. Technol. 31(2): 1002-1008 (2021) - [i5]Hidetoshi Matsuo
Unsupervised-learning-based method for chest MRI-CT transformation using structure constrained unsupervised generative attention networks. CoRR abs/2106.08557 (2021) - 2020
- [j6]Chisako Muramatsu, Mizuho Nishio, Takuma Goto, Mikinao Oiwa, Takako Morita, Masahiro Yakami, Takeshi Kubo, Kaori Togashi, Hiroshi Fujita:
Improving breast mass classification by shared data with domain transformation using a generative adversarial network. Comput. Biol. Medicine 119: 103698 (2020) - [j5]Shunjiro Noguchi, Mizuho Nishio, Masahiro Yakami, Keita Nakagomi, Kaori Togashi:
Bone segmentation on whole-body CT using convolutional neural network with novel data augmentation techniques. Comput. Biol. Medicine 121: 103767 (2020) - [j4]Mizuho Nishio, Chisako Muramatsu, Shunjiro Noguchi, Hirotsugu Nakai, Koji Fujimoto
Attribute-guided image generation of three-dimensional computed tomography images of lung nodules using a generative adversarial network. Comput. Biol. Medicine 126: 104032 (2020) - [j3]Mizuho Nishio, Sho Koyasu
Automatic detection of acute ischemic stroke using non-contrast computed tomography and two-stage deep learning model. Comput. Methods Programs Biomed. 196: 105711 (2020) - [j2]Toru Tanaka
Adaptive Voxel Matching for Temporal CT Subtraction. J. Digit. Imaging 33(6): 1543-1553 (2020) - [i4]Mizuho Nishio, Sho Koyasu, Shunjiro Noguchi, Takao Kiguchi, Kanako Nakatsu, Thai Akasaka, Hiroki Yamada, Kyo Itoh:
Automatic detection of acute ischemic stroke using non-contrast computed tomography and two-stage deep learning model. CoRR abs/2004.04432 (2020) - [i3]Mizuho Nishio, Shunjiro Noguchi, Hidetoshi Matsuo, Takamichi Murakami:
Automatic classification between COVID-19 pneumonia, non-COVID-19 pneumonia, and the healthy on chest X-ray image: combination of data augmentation methods. CoRR abs/2006.00730 (2020)
2010 – 2019
- 2019
- [j1]Yasuhisa Kurata, Mizuho Nishio, Aki Kido
Automatic segmentation of the uterus on MRI using a convolutional neural network. Comput. Biol. Medicine 114 (2019) - [c2]Koji Shimizu, Gakuto Aoyama, Mizuho Nishio, Masahiro Yakami, Takeshi Kubo, Yutaka Emoto, Tatsuya Ito, Tomohiro Kuroda, Hiroyoshi Isoda:
A case study regarding clinical performance evaluation method of medical device software for approval. Image Perception, Observer Performance, and Technology Assessment 2019: 1095210 - [i2]Mizuho Nishio, Koji Fujimoto, Kaori Togashi:
Lung segmentation on chest x-ray images in patients with severe abnormal findings using deep learning. CoRR abs/1908.07704 (2019) - 2017
- [i1]Mizuho Nishio, Mitsuo Nishizawa, Osamu Sugiyama, Ryosuke Kojima, Masahiro Yakami, Tomohiro Kuroda, Kaori Togashi:
Computer-aided diagnosis of lung nodule using gradient tree boosting and Bayesian optimization. CoRR abs/1708.05897 (2017) - 2015
- [c1]Mizuho Nishio, Atsushi K. Kono, Hisanobu Koyama, Tatsuya Nishii
Tumor segmentation on FDG-PET: usefulness of locally connected conditional random fields. Image Processing 2015: 94133P
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