| Radiomics with artificial intelligence for precision medicine in radiation therapy H Arimura, M Soufi, H Kamezawa, K Ninomiya, M Yamada Journal of radiation research 60 (1), 150-157, 2019 | 108 | 2019 |
| Automated classification of urinary stones based on microcomputed tomography images using convolutional neural network LA Fitri, F Haryanto, H Arimura, C YunHao, K Ninomiya, R Nakano, ... Physica Medica 78, 201-208, 2020 | 32 | 2020 |
| Radiomic prediction of radiation pneumonitis on pretreatment planning computed tomography images prior to lung cancer stereotactic body radiation therapy T Hirose, H Arimura, K Ninomiya, T Yoshitake, J Fukunaga, Y Shioyama Scientific reports 10 (1), 20424, 2020 | 30 | 2020 |
| Homological radiomics analysis for prognostic prediction in lung cancer patients K Ninomiya, H Arimura Physica Medica 69, 90-100, 2020 | 23 | 2020 |
| Potentials of radiomics for cancer diagnosis and treatment in comparison with computer-aided diagnosis H Arimura, M Soufi, K Ninomiya, H Kamezawa, M Yamada Radiological physics and technology 11, 365-374, 2018 | 22 | 2018 |
| Robust radiogenomics approach to the identification of EGFR mutations among patients with NSCLC from three different countries using topologically invariant … K Ninomiya, H Arimura, WY Chan, K Tanaka, S Mizuno, ... PloS one 16 (1), e0244354, 2021 | 19 | 2021 |
| Radiomic features based on Hessian index for prediction of prognosis in head-and-neck cancer patients QC Le, H Arimura, K Ninomiya, Y Kabata Scientific reports 10 (1), 21301, 2020 | 10 | 2020 |
| Automated approach for estimation of grade groups for prostate cancer based on histological image feature analysis A Hossain, H Arimura, F Kinoshita, K Ninomiya, S Watanabe, K Imada, ... The Prostate 80 (3), 291-302, 2020 | 6 | 2020 |
| Preoperative and Non-Invasive Approach for Radiomic Biomarker-Based Prediction of Malignancy Grades in Patients with Parotid Gland Cancer in Magnetic Resonance Images H KAMEZAWA, H ARIMURA, R YASUMATSU, K NINOMIYA, S HASEAI Medical Imaging and Information Sciences 37 (4), 66-74, 2020 | 5 | 2020 |
| Relapse predictability of topological signature on pretreatment planning CT images of stage I non‐small cell lung cancer patients before treatment with stereotactic ablative … T Kodama, H Arimura, Y Shirakawa, K Ninomiya, T Yoshitake, ... Thoracic Cancer 13 (15), 2117-2126, 2022 | 4 | 2022 |
| Stratification of prostate cancer patients into low‐and high‐grade groups using multiparametric magnetic resonance radiomics with dynamic contrast‐enhanced image joint histograms A Urakami, H Arimura, Y Takayama, F Kinoshita, K Ninomiya, K Imada, ... The Prostate 82 (3), 330-344, 2022 | 4 | 2022 |
| Feasibility of anatomical feature points for the estimation of prostate locations in the Bayesian delineation frameworks for prostate cancer radiotherapy K Ninomiya, H Arimura, M Sasahara, Y Kai, T Hirose, S Ohga Radiological physics and technology 11, 434-444, 2018 | 4 | 2018 |
| Can Persistent Homology Features Capture More Intrinsic Information about Tumors from 18F-Fluorodeoxyglucose Positron Emission Tomography/Computed … QC Le, H Arimura, K Ninomiya, T Kodama, T Moriyama Metabolites 12 (10), 972, 2022 | 3 | 2022 |
| Synergistic combination of a topologically invariant imaging signature and a biomarker for the accurate prediction of symptomatic radiation pneumonitis before stereotactic … K Ninomiya, H Arimura, T Yoshitake, T Hirose, Y Shioyama PloS one 17 (1), e0263292, 2022 | 3 | 2022 |
| Semi-automated prediction approach of target shifts using machine learning with anatomical features between planning and pretreatment CT images in prostate radiotherapy Y Kai, H Arimura, K Ninomiya, T Saito, Y Shimohigashi, A Kuraoka, ... Journal of radiation research 61 (2), 285-297, 2020 | 3 | 2020 |
| Topology-based radiomic features for prediction of parotid gland cancer malignancy grade in magnetic resonance images K Ikushima, H Arimura, R Yasumatsu, H Kamezawa, K Ninomiya Magnetic Resonance Materials in Physics, Biology and Medicine 36 (5), 767-777, 2023 | 2 | 2023 |
| Three-dimensional topological radiogenomics of epidermal growth factor receptor Del19 and L858R mutation subtypes on computed tomography images of lung cancer patients K Ninomiya, H Arimura, K Tanaka, WY Chan, Y Kabata, S Mizuno, ... Computer Methods and Programs in Biomedicine 236, 107544, 2023 | 2 | 2023 |
| 6. Imaging Biopsy for Assisting Cancer Precision Therapy-Information Extracted from Radiomics H Arimura, T Kodama, A Urakami, H Kamezawa, TA Hirose, K Ninomiya Nihon Hoshasen Gijutsu Gakkai zasshi 78 (2), 219-224, 2022 | 1 | 2022 |
| Homology-based approach for prognostic prediction of lung cancer using novel topologically invariant radiomic features K Ninomiya, H Arimura Medical Imaging 2020: Image Processing 11313, 406-411, 2020 | 1 | 2020 |
| A radiomics study of textural features using magnetic resonance imaging for classification of breast cancer subtypes ZY Tang, LK Tan, BY Ng, K Rahmat, MT Ramli, K Ninomiya, JHD Wong Journal of Physics: Conference Series 1497 (1), 012015, 2020 | 1 | 2020 |
