Nishigaki D, Suzuki Y, Watabe T, Katayama D, Kato H, Wataya T, Kita K, Junya Sato J, Tomiyama N, Kido S. Vision transformer to differentiate between benign and malignant slices in 18F-FDG PET/CT. Scientific Reports. 2024(Apr); 14, 8334.
Shimada R, Sofue K, Ueno Y, Wakayama T, Yamaguchi T, Ueshima E, Kusaka A, Hori M, Murakami T. Utility of Thin-slice Fat-suppressed Single-shot T2-weighted MR Imaging with Deep Learning Image Reconstruction as a Protocol for Evaluating the Pancreas. Magn Reson Med Sci. Published Online: June 21, 2024. doi:10.2463/mrms.mp.2024-0017
Yamaguchi T, Sofue K, Ueshima E, Sugiyama N, Yabe S, Ueno Y, Masuda A, Toyama H, Kodama T, Komatsu M, Hori M, Murakami T. Rim Enhancement on Contrast-Enhanced CT as a Predictor of Prognosis in Patients with Pancreatic Ductal Adenocarcinoma. Diagnostics 2024, 14(8), 782; https://doi.org/10.3390/diagnostics14080782. Published: 9 April 2024
Kinoshita K, Sakai T, Inai K, Noriki S, Hironobu N, Hirano Y, Kido S, Kimura H, Tsujikawa T. Postmortem temporal chest CT and its pathological correlation in piglets The Journal of Medical Investigation. The Journal of Medical Investigation. 2024(Apr).
Wataya T, Miura A, Sakisuka T, Fujiwara M, Tanaka H, Hiraoka Y, Sato J, Tomiyama M, Nishigaki D, Kita K, Suzuki Y, Kido S, Tomiyama N. Comparison of natural language processing algorithms in assessing the importance of head computed tomography reports written in Japanese. Japanese Journal of Radiology. 2024(Apr); 1-12.
Ninomiya K, Yanagawa M, Tsubamoto M, Sato Y, Suzuki Y, Hata A, Kikuchi N, Yoshida Y, Yamagata K, Doi S, Ogawa R, Tokuda Y, Kido S, Tomiyama N. Prediction of solid and micropapillary components in lung invasive adenocarcinoma: radiomics analysis from high-spatial-resolution CT data with 1024 matrix. Japanese Journal of Radiology, 2024(Feb); 1-9.
Kita K, Fujimori T, Suzuki Y, Kaito T, Takenaka S, Kanie Y, Furuya M, Wataya T, Nishigaki D, Sato J, Noriyuki T, Okada S, Kido S. Automated entry of paper-based patient-reported outcomes: Applying deep learning to the Japanese orthopaedic association back pain evaluation questionnaire. Computers in Biology and Medicine, 2024(Feb); 172;101897.
Kita K, Uemura K, Takao M, Fujimori T, Tamura K, Nakamura N, Wakabayashi G, Kurakami H, Suzuki Y, Wataya T, Nishigaki D, Okada S, Tomiyama N, Kido S, Use of Artificial Intelligence to Identify Data Elements for The Japanese Orthopaedic Association National Registry from Operative Records. Journal of Orthopaedic Science 2023 Nov;28(6):1392-1399
Ichiuji Y, Mabu S, Hatta, S, Inai, K, Higuchi, S, Kido, S. Domain transformation using semi-supervised CycleGAN for improving performance of classifying thyroid tissue images. International Journal of Computer Assisted Radiology and Surgery, 2024(Jan); 1-11.
Sato J, Matsumoto T, Nakao R, Tanaka H, Nagahara H, Niioka H, Takamatsu T. Deep UV-Excited Fluorescence Microscopy Installed with CycleGAN-Assisted Image Translation Enhances Precise Detection of Lymph Node Metastasis towards Rapid Intraoperative Diagnosis. Scientific Reports 2023(Nov).
Hatta S, Ichiuji Y, Mabu S, Kugler M, Hontani H, Okoshi T, Fuse H, Kawada T, Kido S, Imamura Y, Naiki H, Inai K. Improved artificial intelligence discrimination of minor histological populations by supplementing with color‐adjusted images. Scientific Reports, 2023(Nov).
Sato Y, Sato J, Tomiyama N, Kido S. High-quality semi-supervised anomaly detection with generative adversarial networks. International Journal of Computer Assisted Radiology and Surgery, 2023(Nov); 1-11.
Gerdprasert T, Mabu S, Kido S. Disease Area Detection for Chest X‐Ray Image Diagnosis Using Deep Learning with Pseudo Labeling and Ensemble Learning. IEEJ Trans, 2023(Nov); 18: 1772 - 1780.
Kita K, Fujimori T, Suzuki Y, Kanie Y, Takenaka S, Kaito T, Taki T, Ukon Y, Furuya M, Saiwai H, Nakajima N, Sugiura T, Ishiguro H, Kamatani T, Tsukazaki H, Sakai Y, Takami H, Tateiwa D, Hashimoto K, Wataya T, Nishigaki D, Sato J, Hoshiyama M, Tomiyama N, Okada S, Kido S. Bimodal artificial intelligence using TabNet for differentiating spinal cord tumors—integration of patient background information and images. iScience, 2023(Oct) ;26(10); 107900.
Suganuma Y, Teramoto A, Saito K, Fujita H, Suzuki Y, Tomiyama N, Kido S. Hybrid Multiple-Organ Segmentation Method Using Multiple U-Nets in PET/CT Images. Applied Sciences, 2023(Sep); 13(19); 10765.
Doi S, Yanagawa M, Matsui T, Hata A, Kikuchi N, Yoshida Y, Yamagata K, Ninomiya K, Kido S, Tomiyama, N. Usefulness of Three-Dimensional Iodine Mapping Quantified by Dual-Energy CT for Differentiating Thymic Epithelial Tumors. Journal of Clinical Medicine, 2023(Aug); 12(17); 5610.
Sato J, Suzuki Y, Wataya T, Nishigaki D, Kita K, Yamagata K, Tomiyama N, Kido S. Anatomy-aware Self-supervised Learning for Anomaly Detection in Chest Radiographs. iScience, 2023(Jun) ;26: 107086.
Koike H, Ashizawa K, Tsutsui S, Kurohama Y, Okano S, Nagayasu T, Kido S, Uetani M, Toya R. Differentiation between heterogeneous GGN and part-solid nodule using 2 D grayscale histogram analysis of thin-section CT image. Clinical Lung Cancer, 2023. https://doi.org/10.1016/j.cllc.2023.06.001
Yabe S, Sofue K, Hori M, Maebayashi T, Nishigaki M, Tsujita Y, Yamaguchi T, Ueshima E, Ueno Y, Murakami T. Added value of contrast enhancement boost images in routine multiphasic contrast-enhanced CT. Eur J Radiol 2023 Mar;160:110696. doi: 10.1016/j.ejrad.2023.110696. Epub 2023 Jan 12.
Fukutomi A, Sofue K, Ueshima E, Negi N, Ueno Y, Tsujita Y, Yabe S, Yamaguchi T, Shimada R, Kusaka A, Hori M, Murakami T. Deep learning image reconstruction to improve accuracy of iodine quantification and image quality in dual-energy CT of the abdomen: a phantom and clinical study. Eur Radiol. 2023 Feb;33(2):1388-1399. doi: 10.1007/s00330-022-09127-1.
Nishigaki D, Suzuki Y, Wataya T, Kita K, Yamagata K, Sato J, Kido S, Tomiyama N. BERT-based Transfer Learning in Sentence-level Anatomical Classification of Free-text Radiology Reports. Radiology: Artificial Intelligence, 2023(Feb);5(2): e220097.
Wataya T, Yanagawa M, Tsubamoto M, Sato T, Nishigaki D, Kita K, Yamagata K, Suzuki Y, Hata A, Kido S, Tomiyama N. Radiologists with and without deep learning-based computer-aided diagnosis: comparison of performance and interobserver agreement for characterizing and diagnosing pulmonary nodules/masses. European Radiology, 2023(Jan); 33(1): 348-359.
Kido S. Radiologists with and without deep learning-based computer-aided diagnosis. AI-blog, 2022(Oct). https://ai.myesr.org/articles/radiologists-with-and-without-deep-learning-based-computer-aided-diagnosis/
Kita K, Uemura K, Takao M, Fujimori T, Tamura K, Nakamura N, Wakabayashi G, Kurakami H, Suzuki Y, Wataya T, Nishigaki D, Okada S, Tomiyama N, Kido S. Use of artificial intelligence to identify data elements for The Japanese Orthopaedic Association National Registry from operative records. Journal of Orthopaedic Science, 2022(Sep); https://doi.org/10.1016/j.jos.2022.09.003.
Fujimori T, Suzuki Y, Takenaka S, Kita K, Kanie Y, Kaito T, Ukon Y, Watabe T, Nakajima N, Kido S, Okada S. Development of artificial intelligence for automated measurement of cervical lordosis on lateral radiographs. Scientific Reports, 2022(Sep); 12(1):1-11.
Miyake N, Lu H, Kamiya T, Aoki T, Kido S. Temporal Subtraction Technique for Thoracic MDCT Based on Residual VoxelMorph. Applied Sciences, 2022 (Aug); 12(17):8542.
Nakamoto A, Hori M, Onishi H, Ota T, Fukui H, Ogawa K, Masumoto J, Kudo A, Kitamura Y, Kido S, Tomiyama N. Three-dimensional conditional generative adversarial network-based virtual thin-slice technique for the morphological evaluation of the spine. Scientific Reports, 2022(Jul); 12(1):1-8.
Kataoka Y, Baba T, Ikenoue T, Matsuoka Y, Matsumoto J, Kumasawa J, Tochitani K, Funakoshi H, Hosoda T, Kugimiya A, Shirano M, Hamabe F, Iwata S, Kitamura Y, Goto T, Handa T, Kido S, Fukuma S, Tomiyama N, Hirai T, Ogura T. Development and external validation of a deep learning-based computed tomography classification system for COVID-19. Annals of Clinical Epidemiology, 2022(Jul); 22014.
Kido S, Kidera S, Hirano Y, Mabu S, Kamiya T, Tanaka N, Suzuki Y, Yanagawa M, Tomiyama N. Segmentation of Lung Nodules on CT Images Using a Nested Three-Dimensional Fully Convolutional Network. Frontiers in Artificial Intelligence, 2022(Feb); 5: 782225.
Yamaguchi T, Sofue K, Ueshima E, Ueno Y, Tsujita Y, Yabe S, Shirakawa S, Toyama H, Hori M, Fukumoto T, Murakami T. Abbreviated Gadoxetic Acid-Enhanced MRI for the Detection of Liver Metastases in Patients With Potentially Resectable Pancreatic Ductal Adenocarcinoma. J Magn Reson Imaging. 2022, 56:725-736. doi: 10.1002/jmri.28059. PMID: 35005813.
Suzuki Y, Kido S, Mabu S, Yanagawa M, Tomiyama N, Sato Y. Segmentation of Diffuse Lung Abnormality Patterns on Computed Tomography Images using Partially Supervised Learning. Advanced Biomedical Engineering, 2022; 11:25-36.
Wu J, Furuzuki M, Li G, Kamiya T, Mabu S, Tanabe M, Ito K, Kido S. Segmentation of liver tumors in multiphase computed tomography images using hybrid method. Computers & Electrical Engineering. 2022(Jan); 97: 107626.
Kido S, Mabu S, Kamiya T, Hirano Y, Tachibana R, Inai K. Clinical Applications of MCA to Diagnosis. In Multidisciplinary Computational Anatomy, Springer, Singapore. 2022; 89-96.
Suzuki Y, Hori M, Kido S, Otake Y, Ono M, Tomiyama N, Sato Y. Comparative Study of Vessel Detection Methods for Contrast Enhanced Computed Tomography: Effects of Convolutional Neural Network Architecture and Patch Size. Advanced Biomedical Engineering, 2021; 10:138-149.
Mabu S, Miyake M, Kuremoto T, Kido S. Semi-supervised CycleGAN for domain transformation of chest CT images and its application to opacity classification of diffuse lung diseases. International Journal of Computer Assisted Radiology and Surgery. 2021( Oct); 1-11.
Asatani N, Kamiya T, Mabu S, Kido S. Classification of respiratory sounds using improved convolutional recurrent neural network. Comput Electr Eng. 2021( Sep);94:107367.
Ota T, Hori M, Le Bihan D, Fukui H, Onishi H, Nakamoto A, Tsuboyama T, Tatsumi M, Ogawa K, Tomiyama N. Diffusion-based virtual MR elastography of the liver: Can it be extended beyond liver fibrosis? J Clin Med. Sep 2021, 10, 4553. doi: 10.3390/jcm10194553
Ogawa K, Onishi H, Hori M, Nakamoto A, Ota T, Fukui H, Tatsumi M, Enchi Y, Sato K, Kaketaka K, Tomiyama N. Visualization of small visceral arteries on abdominal CT angiography using ultra-high-resolution CT scanner. Jpn J Radiol. 39(9):889-897, 2021. doi: 10.1007/s11604-021-01124-6. Epub 2021 May 4. PMID: 33948788.
Ota T, Hori M, Sasaki K, Onishi H, Nakamoto A, Tatsumi M, Fukui H, Ogawa K, Tomiyama N. Multimaterial decomposition algorithm for quantification of fat in hepatocellular carcinoma using rapid kilovoltage-switching dual-energy CT: A comparison with chemical-shift MR imaging. Medicine. 100(20):e26109. May 2021. doi: 10.1097/MD.0000000000026109
Nogami M, Zeng F, Inukai J, Watanabe Y, Nishio M, Kanda T, Ueno YR, Sofue K, Kono AK, Hori M, Ohnishi A, Kubo K, Kurimoto T, Murakami T. Physiological skin FDG uptake: A quantitative and regional distribution assessment using PET/MRI. PLoS One. 26;16(3):e0249304. Mar 2021. doi: 10.1371/journal.pone.0249304
Kojita Y, Matsuo H, Kanda T, Nishio M, Sofue K, Nogami M, Kono AK, Hori M, Murakami T. Deep learning model for predicting gestational age after the first trimester using fetal MRI. Eur Radiol. 2021 Jun;31(6):3775-3782. doi: 10.1007/s00330-021-07915-9. Epub 2021 Apr 14.
Miyake N, Lu H, Kamiya T, Aoki T, Kido S. Optimizing early cancer diagnosis and detection using a temporal subtraction technique. Technological Forecasting and Social Change. 2021(Jun); 167: 120745.
Yanagawa M, Niioka H, Kusumoto M, Awai K, Tsubamoto M, Satoh Y, Miyata T, Yoshida Y, Kikuchi N, Hata A, Yamasaki S, Kido S, Nagahara H, Miyake J, Tomiyama N. Diagnostic performance for pulmonary adenocarcinoma on CT: comparison of radiologists with and without three-dimensional convolutional neural network. European Radiology. 2021(Apr);31(4):1978-86.
Hata A, Yanagawa M, Yamagata K, Suzuki Y, Kido S, Kawata A, Doi S, Yoshida Y, Miyata T, Tsubamoto M, Kikuchi N, Tomiyama N. Deep learning algorithm for detection of aortic dissection on non-contrast-enhanced CT. European Radiology. 2021(Jan);31(2):1151-59.
Matsuo H, Nishio M, Kanda T, Kojita Y, Kono K, Hori M, Teshima M, Otsuki N, Nibu K, Murakami T. Diagnostic accuracy of deep-learning with anomaly detection for a small amount of imbalanced data: Discriminating malignant parotid tumors in MRI. Sci Rep 10(1): 19388, November 2020. DOI: 10.1038/s41598-020-76389-4
Tsujita Y, Sofue K, Komatsu S, Yamaguchi T, Ueshima E, Ueno Y, Kanda T, Okada T, Nogami M, Yamaguchi M, Tsurusaki M, Hori M, Fukumoto T, Murakami T. Prediction of post-hepatectomy liver failure using gadoxetic acid-enhanced magnetic resonance imaging for hepatocellular carcinoma with portal vein invasion. Eur J Radiol 2020 Sep;130:109189. doi: 10.1016/j.ejrad.2020.109189. Epub 2020 Jul 24.
Urase Y, Nishio M, Ueno Y, Kono A, Sofue K, Kanda T, Maeda T, Nogami M, Hori M, Murakami T. Simulation Study of Low-Dose Sparse-Sampling CT with Deep Learning-Based Reconstruction: Usefulness for Evaluation of Ovarian Cancer Metastasis. Appl Sci 10, 4446, Jun 2020. doi:10.3390/app10134446
Kromrey ML, Hori M, Goshima S, Kozaka K, Hyodo T, Nakamura Y, Nishie A, Tamada T, Shimizu T, Kanki A, Motosugi U. Gadoxetate disodium-related event during image acquisition: a prospective multi-institutional study for better MR practice. Eur Radiol 30(1):281-290, Jan 2020. doi: 10.1007/s00330-019-06358-7.
Soufi M, Otake Y, Hori M, Moriguchi K, Imai Y, Sawai Y, Ota T, Tomiyama N, Sato Y. Liver shape analysis using partial least squares regression-based statistical shape model: application for understanding and staging of liver fibrosis. Int J Comput Assist Radiol Surg 14(12):2083-2093, Dec 2019. doi: 10.1007/s11548-019-02084-z.
Mabu S, Kido S, Hirano Y, Kuremoto T. Opacity Labeling of Diffuse Lung Diseases in CT Images Using Unsupervised and Semi-supervised Learning. Deep Learning in Healthcare. In Intelligent Systems Reference Library, Springer, Cham. 2020; 171:165-79.
Suzuki A, Sakanashi H, Kido S, Shouno H. Deep Learning in Textural Medical Image Analysis. Deep Learning in Healthcare. In Intelligent Systems Reference Library, Springer, Cham. 2020; 171:111-26.
Kido S, Hirano Y, Mabu S. Deep Learning for Pulmonary Image Analysis: Classification, Detection, and Segmentation. Deep Learning in Medical Image Analysis. In Advances in Experimental Medicine and Library, Springer, Cham. 2020;1213: 47-58.
Wataya T, Nakanishi K, Suzuki Y, Kido S, Tomiyama N. Introduction to deep learning: minimum essence required to launch a research. Japanese Journal of Radiology. 2020(Jun);38(10):907-21.
Mabu S, Atsumo A, Kido S, Kuremoto T, Hirano Y. Investigating the Effects of Transfer Learning on ROI-based Classification of Chest CT Images: A Case Study on Diffuse Lung Diseases. Journal of Signal Processing Systems. 2020(Mar);92(3):307-13.
Lu H, Kondo M, Li Y, Tan J, Kim H, Murakami S, Aoki T, Kido S. Supervoxel graph cuts: an effective method for ggo candidate regions extraction on ct images. IEEE Consumer Electronics Magazine. 2019(Dec);9(1):61-6.
Xu R, Cong Z, Xinchen Ye, Hirano Y, Kido S, Gyobu T, Kawata Y, Honda O, Tomiyama N. Pulmonary Textures Classification via a Multi-Scale Attention Network. IEEE Journal of Biomedical and Health Informatics. 2019(Nov);24(7):2041-52.
Kido S, Kita K, Nishigaki D, Tomiyama N. Application of natural language processing in AI-CAD. International Workshop on Advanced Image Technology 2024. 2024年1月7日. Langkawi, Malaysia.
Hori M, Sofue K, Akino N, Nishigaki M, Yabe S, Yamaguchi T, Ueshima E, Murakami T. High resolution CT imaging with a 1024 matrix: Impact of matrix size, slice thickness, reconstruction algorithm, and reslicing on radiomic feature quantification in hepatocellular carcinoma. Radiological Society of North America. 109th Scientific Assembly and Annual Meeting. November 26 - 30, 2023, Chicago.
Maebayashi T, Hori M, Akino N, Sofue K, Kagawa K, Fukutomi A, Negi N, Oribe T, Kusaka A, Murakami T. Phantom study on radiomic features in ultra-high-resolution CT imaging: Matrix size, radiation dose, and reconstruction algorithms. Radiological Society of North America. 109th Scientific Assembly and Annual Meeting. November 26 - 30, 2023, Chicago.
Yabe S, Hori M, Sofue K, Maebayashi T, Kawai K, Nishigaki M, Yamaguchi T, Ueshima E, Ueno Y, Murakami T. Assessing the efficacy of multiple aAdditive processing in Contrast Enhancement Boost CT technique for the diagnosis of hypervascular hepatocellular carcinoma. Radiological Society of North America. 109th Scientific Assembly and Annual Meeting. November 26 - 30, 2023, Chicago.
Ishikawa K, Fukutomi A, Kagawa K, Negi N, Kusaka A, Hori M, Murakami T. Comparison of imaging methods for ultra-high resolution CT to delineate very small vessels - Low tube voltage imaging vs. small focal spot imaging. Radiological Society of North America. 109th Scientific Assembly and Annual Meeting. November 26 - 30, 2023, Chicago.
Sato J, Kido S. Large Patch size Training for Pediatric Neuroblastoma Segmentation. MICCAI SPPIN2023 challenge session. 2023年10月8日. Vancouver, Canada.
Kita K, Takahito F, Suzuki Y, Okada S, Kido S. Bimodal Artificial Intelligence Differentiating Spinal Tumors based on Integrated Magnetic Resonance Imaging and Patient Information. Spineweek2023. 2023年5月3日．Melbourne, Australia.
Yabe S, Sofue K, Hori M, Maebayashi T, Nishigaki M, Tsujita T, Yamaguchi T, Ueshima E, Murakami T. Usefulness of the Contrast Enhancement Boost technique combined with virtual monoenergetic images in dual-energy CT for the evaluation of hypervascular hepatocellular carcinoma. European Congress of Radiology (ECR) 2023. March 1-5, 2023. Vienna.
Kita K, Takahito T, Suzuki Y, Okada S, Kido S. Bi-Modal Network Combining Convolutional Neural Network and TabNet, Differentiating Spinal Tumors based on Images and Clinical Risk Factors. Society of Photo-Optical Instrumentation Engineers Medical Imaging 2023. 2023年2月20日．San Diego, California, United States.
Hori M, Sofue K, Yabe S, Nishigaki M, Akino N, Yamaguchi T, Tsujita Y, Ueshima E, Negi N, Kusaka A, Murakami T. Advanced CT techniques in the evaluation of hepatocellular carcinoma: Roles of ultra-high-resolution CT, dual-energy CT, contrast enhancement boost technique, and radiomics. Radiological Society of North America. 108th Scientific Assembly and Annual Meeting. November 27 - December 1, 2022, Chicago.
Hori M, Sofue K, Akino N, Nishigaki M, Yabe S, Yamaguchi T, Tsujita Y, Ueshima E, Murakami T. Radiomic Features of Hepatocellular Carcinoma at Ultra-High-Resolution CT with a 1024 Matrix: Dependencies on Matrix Size and Reconstruction Algorithm. Radiological Society of North America. 108th Scientific Assembly and Annual Meeting. November 27 - December 1, 2022, Chicago.
Kido S. Artificial Intelligence Diagnostic Radiology：Current Technology and Future Directions. 7th Osaka University-Samsung Medical Center Radiology Forum. 2022年11月18日．Online.
Sato J, Kido S. Large Patch Size and Batch Size Improve Performance in Multi-Organ Segmentation. MICCAI2022. 2022年9月18日．Singapore.
Yabe S, Sofue K, Hori M, Maebayashi T, Nishigaki M, Tsujita T, Yamaguchi T, Ueshima E, Murakami T. Added Value of CE-Boost Images in Routine Multiphasic Contrast-Enhanced CT in the Diagnosis of Small Hypervascular Hepatocellular Carcinoma. European Congress of Radiology (ECR) 2022. March 2-6, 2022. online; July 13-17, 2022. Vienna. Obtained the Scientific Exhibition Award: Certificate of Merit.
Maebayashi T, Hori M, Murakami T, Sofue K, Kagawa K, Kusaka A, Nishigaki M, Fukutomi N. Is Auto Exposure Control Useful in Iodine Concentration Measurements using a rapid kV-switching Dual Energy CT?: A Phantom Study. European Congress of Radiology (ECR) 2022. March 2-6, 2022. online; July 13-17, 2022. Vienna.
Kido S. Segmentation of Pulmonary Abnormalities on CT Images Using Deep Learning. Dalian University of Technology and Osaka University Symposium on AI&Healthcare. 2022年1月14日．online.
Hori M, Sofue K, Yabe S, Nishigaki M, Negi N, Yamaguchi T, Tsujita Y, Ueshima E, Ueno Y, Kusaka A, Murakami T. Ultra-High-Resolution CT with 1024-Matrix using a Novel Deep Learning Reconstruction Technique: How to use it for Abdominal Imaging. Radiological Society of North America. 107th Scientific Assembly and Annual Meeting. November 28 - December 2, 2021, Chicago.
Hori M, Sofue K, Yabe S, Nishigaki M, Maebayashi T, Yamaguchi T, Tsujita Y, Ueshima E, Ueno Y, Kusaka A, Murakami T. Principles and Clinical Utility of a Novel Contrast Enhancement Boost Technique for Abdominal CT. Radiological Society of North America. 107th Scientific Assembly and Annual Meeting. November 28 - December 2, 2021, Chicago.
Masaki Y, Otake Y, Soufi M, Hori M, Onishi H, Tomiyama N, Sato Y. Analysis of multiplanar fusion based on uncertainty estimation in automatic segmentation of abdominal organs in 3D CT image using 2D Bayesian U-Net. International Forum on Medical Imaging in Asia 2021 (IFMIA 2021), January 24-27, 2021, Online Conference. (Proceedings of the SPIE, Volume 11792, id. 1179208 6 pp. 2021. doi:10.1117/12.2590794)
Kido S, Kidera S, Suzuki Y, Yanagawa M, Tomiyama N, Hirano Y, Tanaka N. Segmentation of Pulmonary Nodules on 3D-CT Images using Deep Learning. ECR2020. 2020年7月15-19日．EPOS C-03282. online.
Suzuki Y, Yamagata K, Yanagawa M, Kido S, Tomiyama N. Weak supervision in convolutional neural network for semantic segmentation of diffuse lung diseases using partially annotated dataset. The International Society for Optics and Phonics Medical Imaging Forum 2020. 2020年2月17日．Houston, Texas, United States.
Kido S, Suzuki Y, Tomiyama N. Segmentation of Pulmonary Abnormalities on CT Images using Deep Learning. International Workshop on Advanced Image Technology 2020. 2020年1月5日．Yogyakarta, Indonesia.
Kido S. Current status and issues for application of artificial intelligence on diagnostic imaging for pulmonary images. 2019年10月23日. 大連理工大学, 大連, 中国.
日本生体医工学会論文賞・阪本賞. Suzuki Y, Hori M, Kido S, Otake Y, Ono M, Tomiyama N, Sato Y. Comparative Study of Vessel Detection Methods for Contrast Enhanced Computed Tomography: Effects of Convolutional Neural Network Architecture and Patch Size. 第６２回日本生体医工学会大会．2023年5月19日．名古屋．
Scientific Exhibition Award: Certificate of Merit. European Congress of Radiology (ECR) 2022. March 2-6, 2022. online; July 13-17, 2022, Vienna: Yabe S, Sofue K, Hori M, Maebayashi T, Nishigaki M, Tsujita T, Yamaguchi T, Ueshima E, Murakami T. Added Value of CE-Boost Images in Routine Multiphasic Contrast-Enhanced CT in the Diagnosis of Small Hypervascular Hepatocellular Carcinoma.
Best Paper Award. International Forum on Medical Imaging in Asia 2021 (IFMIA 2021), January 24-27, 2021, Online Conference: Masaki Y, Otake Y, Soufi M, Hori M, Onishi H, Tomiyama N, Sato Y. Analysis of multiplanar fusion based on uncertainty estimation in automatic segmentation of abdominal organs in 3D CT image using 2D Bayesian U-Net.
第76回日本放射線技術学会総会学術大会. CyPos賞 Bronze Award: Ueda J, Hori M, Sato K, Enchi Y, Fujino K, Tanaka H, Tomiyama N. Radiation dose metrics in CT examinations using japan medical image database (J-MID). 2020年5月15日-6月14日. WEB開催.