K. Ninomiya

发表

Radiomic features based on Hessian index for prediction of prognosis in head-and-neck cancer patients

H. Arimura, Q. Le, K. Ninomiya, 2020, Scientific Reports.

Radiomic prediction of radiation pneumonitis on pretreatment planning computed tomography images prior to lung cancer stereotactic body radiation therapy

H. Arimura, Y. Shioyama, T. Yoshitake, 2020, Scientific Reports.

Automated approach for estimation of grade groups for prostate cancer based on histological image feature analysis

Md. Alamgir Hossain, H. Arimura, Y. Oda, 2019, The Prostate.

Homological radiomics analysis for prognostic prediction in lung cancer patients.

H. Arimura, K. Ninomiya, 2019, Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics.

Radiomics with artificial intelligence for precision medicine in radiation therapy

Hidetaka Arimura, Mazen Soufi, Kenta Ninomiya, 2018, Journal of radiation research.

Prediction Models of Tumor Growth Trajectories Based on Pretreatment CT Images of TKI-Treated Lung Cancer Patients

H. Arimura, Q. Le, K. Ninomiya, 2021 .

Automated classification of urinary stones based on microcomputed tomography images using convolutional neural network.

Hidetaka Arimura, Freddy Haryanto, Kenta Ninomiya, 2020, Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics.

Radiomics-based malignancy prediction of parotid gland tumor

Hidetaka Arimura, Kenta Ninomiya, Hidemi Kamezawa, 2019, Other Conferences.

Semi-automated prediction approach of target shifts using machine learning with anatomical features between planning and pretreatment CT images in prostate radiotherapy

Tetsuo Saito, Hidetaka Arimura, Masato Maruyama, 2020, Journal of radiation research.

Relapse predictability of topological signature on pretreatment planning CT images of stage I non-small cell lung cancer patients before treatment with stereotactic ablative radiotherapy.

H. Arimura, Y. Shioyama, T. Yoshitake, 2022, Thoracic cancer.

Can Persistent Homology Features Capture More Intrinsic Information about Tumors from 18F-Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography Images of Head and Neck Cancer Patients?

H. Arimura, Q. Le, K. Ninomiya, 2022, Metabolites.

Low-lying electronic states of the ferrous high-spin (S=2) heme in deoxy-Mb and deoxy-Hb studied by highly-sensitive multi-frequency EPR.

H. Hori, T. Kida, M. Hagiwara, 2011, Journal of inorganic biochemistry.

Potentials of radiomics for cancer diagnosis and treatment in comparison with computer-aided diagnosis

Hidetaka Arimura, Masahiro Yamada, Mazen Soufi, 2018, Radiological Physics and Technology.