Special Issue on “Machine Learning/Deep Learning in Medical Image Processing” by Mizuho Nishio

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Heterogeneity in pulmonary emphysema: Analysis of CT attenuation using Gaussian mixture model. by Mizuho Nishio, Yutaka Tanaka

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Optimizing statistical evaluation of multiclass classification in diagnostic radiology: a study of the two-parameter multidimensional nominal response model by Mizuho Nishio, Eiji Ota

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Automatic Pancreas Segmentation Using Coarse-Scaled 2D Model of Deep Learning: Usefulness of Data Augmentation and Deep U-Net by Mizuho Nishio, Shunjiro Noguchi, Koji Fujimoto

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Estimation of lung cancer risk using homology-based emphysema quantification in patients with lung nodules. by Mizuho Nishio, Takeshi Kubo, Kaori Togashi

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Lung Cancer Segmentation With Transfer Learning: Usefulness of a Pretrained Model Constructed From an Artificial Dataset Generated Using a Generative Adversarial Network by Mizuho Nishio, Mizuho Nishio, Koji Fujimoto, Koji Fujimoto, Hidetoshi Matsuo, Chisako Muramatsu, Ryo Sakamoto, Ryo Sakamoto, Hiroshi Fujita

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Convolutional neural networks: an overview and application in radiology by Rikiya Yamashita, Mizuho Nishio, Richard Kinh Gian Do, Kaori Togashi

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Comparison between pystan and numpyro in Bayesian item response theory: evaluation of agreement of estimated latent parameters and sampling performance by Mizuho Nishio, Eiji Ota, Hidetoshi Matsuo, Takaaki Matsunaga, Aki Miyazaki, Takamichi Murakami

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Computer-aided diagnosis of lung nodule classification between benign nodule, primary lung cancer, and metastatic lung cancer at different image size using deep convolutional neura... by Mizuho Nishio, Osamu Sugiyama, Masahiro Yakami, Syoko Ueno, Takeshi Kubo, Tomohiro Kuroda, Kaori Togashi

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Automated prediction of emphysema visual score using homology-based quantification of low-attenuation lung region. by Mizuho Nishio, Kazuaki Nakane, Takeshi Kubo, Masahiro Yakami, Yutaka Emoto, Mari Nishio, Kaori Togashi

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Computer-aided diagnosis of lung nodule using gradient tree boosting and Bayesian optimization. by Mizuho Nishio, Mitsuo Nishizawa, Osamu Sugiyama, Ryosuke Kojima, Masahiro Yakami, Tomohiro Kuroda, Kaori Togashi

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Unsupervised-learning-based method for chest MRI–CT transformation using structure constrained unsupervised generative attention networks by Hidetoshi Matsuo, Mizuho Nishio, Munenobu Nogami, Feibi Zeng, Takako Kurimoto, Sandeep Kaushik, Florian Wiesinger, Atsushi K. Kono, Takamichi Murakami

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Fully automatic summarization of radiology reports using natural language processing with large language models by Mizuho Nishio, Takaaki Matsunaga, Hidetoshi Matsuo, Munenobu Nogami, Yasuhisa Kurata, Koji Fujimoto, Osamu Sugiyama, Toshiaki Akashi, Shigeki Aoki, Takamichi Murakami

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Simulation Study of Low-Dose Sparse-Sampling CT with Deep Learning-Based Reconstruction: Usefulness for Evaluation of Ovarian Cancer Metastasis by Yasuyo Urase, Mizuho Nishio, Yoshiko Ueno, Atsushi K. Kono, Keitaro Sofue, Tomonori Kanda, Takaki Maeda, Munenobu Nogami, Masatoshi Hori, Takamichi Murakami

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Development and web deployment of prediction model for pulmonary arterial pressure in chronic thromboembolic pulmonary hypertension using machine learning. by Takaaki Matsunaga, Atsushi Kono, Mizuho Nishio, Takahiro Yoshii, Hidetoshi Matsuo, Mai Takahashi, Takuya Takahashi, Yu Taniguchi, Hidekazu Tanaka, Kenichi Hirata, Takamichi Murakami

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Automatic segmentation of uterine endometrial cancer on multi-sequence MRI using a convolutional neural network by Yasuhisa Kurata, Mizuho Nishio, Yusaku Moribata, Aki Kido, Yuki Himoto, Satoshi Otani, Koji Fujimoto, Masahiro Yakami, Sachiko Minamiguchi, Masaki Mandai, Yuji Nakamoto

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Deep learning model for the automatic classification of COVID-19 pneumonia, non-COVID-19 pneumonia, and the healthy: a multi-center retrospective study by Mizuho Nishio, Daigo Kobayashi, Eiko Nishioka, Hidetoshi Matsuo, Yasuyo Urase, Koji Onoue, Reiichi Ishikura, Yuri Kitamura, Eiro Sakai, Masaru Tomita, Akihiro Hamanaka, Takamichi Murakami

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Automatic segmentation of bladder cancer on MRI using a convolutional neural network and reproducibility of radiomics features: a two-center study by Yusaku Moribata, Yasuhisa Kurata, Mizuho Nishio, Aki Kido, Satoshi Otani, Yuki Himoto, Naoko Nishio, Akihiro Furuta, Hiroyuki Onishi, Kimihiko Masui, Takashi Kobayashi, Yuji Nakamoto

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Stromal area differences with epithelial-mesenchymal transition gene changes in conjunctival and orbital mucosa-associated lymphoid tissue lymphoma by Mizuki Tagami, Mizuki Tagami, Hiroaki Kasashima, Anna Kakehashi, Atsuko Yoshikawa, Mizuho Nishio, Norihiko Misawa, Atsushi Sakai, Hideki Wanibuchi, Masakazu Yashiro, Atsushi Azumi, Shigeru Honda

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Computer-aided diagnosis of chest X-ray for COVID-19 diagnosis in external validation study by radiologists with and without deep learning system by Aki Miyazaki, Kengo Ikejima, Mizuho Nishio, Minoru Yabuta, Hidetoshi Matsuo, Koji Onoue, Takaaki Matsunaga, Eiko Nishioka, Atsushi Kono, Daisuke Yamada, Ken Oba, Reiichi Ishikura, Takamichi Murakami

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