TORU HIGAKI

Last Updated :2025/05/09

Affiliations, Positions
Graduate School of Advanced Science and Engineering, Associate Professor
Web Site
http://vis.hiroshima-u.ac.jp/
Self-introduction
My speciality is image engineering, especially medical image processing is my main research topic.

Basic Information

Academic Degrees

  • Doctor of Engineering, Hiroshima University
  • Master of Engineering, Hiroshima University

Research Fields

  • Complex systems;Biomedical engineering;Medical systems

Research Keywords

  • Medical image processing

Educational Activity

Course in Charge

  1. 2025, Undergraduate Education, Intensive, Practice for medical research
  2. 2025, Undergraduate Education, Intensive, Practice of Medicine I
  3. 2025, Undergraduate Education, Intensive, Practice of Medicine II
  4. 2025, Undergraduate Education, 2Term, Image Processing
  5. 2025, Undergraduate Education, 1Term, Informatics and Data Science Exercise I
  6. 2025, Undergraduate Education, Intensive, Long-term Fieldwork I
  7. 2025, Undergraduate Education, 1Term, Intelligence Science Seminar I
  8. 2025, Undergraduate Education, 2Term, Intelligence Science Seminar II
  9. 2025, Undergraduate Education, Second Semester, Graduation Thesis
  10. 2025, Graduate Education (Master's Program) , 1Term, Special Exercises on Informatics and Data Science A
  11. 2025, Graduate Education (Master's Program) , 2Term, Special Exercises on Informatics and Data Science A
  12. 2025, Graduate Education (Master's Program) , 3Term, Special Exercises on Informatics and Data Science B
  13. 2025, Graduate Education (Master's Program) , 4Term, Special Exercises on Informatics and Data Science B
  14. 2025, Graduate Education (Master's Program) , Year, Special Study on Informatics and Data Science
  15. 2025, Graduate Education (Doctoral Program) , Year, Special Study on Informatics and Data Science
  16. 2025, Undergraduate Education, First Semester, International Co-creation Workshop

Research Activities

Academic Papers

  1. Acquiring Spectral Scattering Properties of Seawater from an RGB Image, Proc. 2023 International Workshop on Advanced Image Technology (IWAIT 2023), 20230109
  2. Reproduction of Color Vision Deficiency Considering Spectrum, Proc. 2023 International Workshop on Advanced Image Technology (IWAIT 2023), 20230109
  3. Utility of Wavelet Denoising with Geometry Factor Weighting for Gadoxetic Acid-enhanced Hepatobiliary-phase MR Imaging, MAGNETIC RESONANCE IN MEDICAL SCIENCES, 22(2), 241-252, 2023
    Link to Paper Search Results by DOI
  4. An introduction to photon-counting detector CT (PCD CT) for radiologists, JAPANESE JOURNAL OF RADIOLOGY, 41(3), 266-282, 202303
    Link to Paper Search Results by DOI
  5. Performance of Ultra-High-Resolution Computed Tomography in Super High-Resolution Mode at the Routine Radiation Dose: Phantom Study, JOURNAL OF COMPUTER ASSISTED TOMOGRAPHY, 46(6), 900-905, 2022
    Link to Paper Search Results by DOI
  6. Usefulness of the patient-specific contrast enhancement optimizer simulation software during the whole-body computed tomography angiography, HEART AND VESSELS, 37(8), 1446-1452, 202208
    Link to Paper Search Results by DOI
  7. Dual-energy CT: minimal essentials for radiologists, JAPANESE JOURNAL OF RADIOLOGY, 40(6), 547-559, 202206
    Link to Paper Search Results by DOI
  8. Utility of Radial Scanning for the Identification of Arterial Hypervascularity of Hepatocellular Carcinoma on Gadoxetic Acid-Enhanced Magnetic Resonance Images, JOURNAL OF COMPUTER ASSISTED TOMOGRAPHY, 45(3), 359-366, 2021
    Link to Paper Search Results by DOI
  9. Prediction of Aortic Contrast Enhancement on Dynamic Hepatic Computed Tomography-Performance Comparison of Machine Learning Methods and Simulation Software, JOURNAL OF COMPUTER ASSISTED TOMOGRAPHY, 46(2), 183-189, 2022
    Link to Paper Search Results by DOI
  10. Re-evaluation of detectability of liver metastases by contrast-enhanced CT: added value of hepatic arterial phase imaging, JAPANESE JOURNAL OF RADIOLOGY, 32(8), 467-475, 201408
    Link to Paper Search Results by DOI
  11. Measurement of Electron Density and Effective Atomic Number by Dual-Energy Scan Using a 320-Detector Computed Tomography Scanner with Raw Data-Based Analysis: A Phantom Study, JOURNAL OF COMPUTER ASSISTED TOMOGRAPHY, 38(6), 824-827, 2014
  12. A new technique for noise reduction at coronary CT angiography with multi-phase data-averaging and non-rigid image registration, EUROPEAN RADIOLOGY, 25(1), 41-48, 201501
    Link to Paper Search Results by DOI
  13. Radiation dose reduction for coronary artery calcium scoring at 320-detector CT with adaptive iterative dose reduction 3D, INTERNATIONAL JOURNAL OF CARDIOVASCULAR IMAGING, 31(5), 1045-1052, 201506
    Link to Paper Search Results by DOI
  14. Clinical utility of gadoxetate disodium-enhanced hepatic MRI for stereotactic body radiotherapy of hepatocellular carcinoma, JAPANESE JOURNAL OF RADIOLOGY, 33(10), 627-635, 201510
    Link to Paper Search Results by DOI
  15. Cerebral blood flow in transient hypothyroidism after thyroidectomy: Arterial spin labeling magnetic resonance study, NEUROENDOCRINOLOGY LETTERS, 36(6), 545-551, 2015
  16. Changes in the regional cerebral blood flow detected by arterial spin labeling after 6-week escitalopram treatment for major depressive disorder, JOURNAL OF AFFECTIVE DISORDERS, 194, 135-143, 201604
    Link to Paper Search Results by DOI
  17. Effect of the Motion Correction Technique on Image Quality at 320-Detector Computed Tomography Coronary Angiography in Patients With Atrial Fibrillation, JOURNAL OF COMPUTER ASSISTED TOMOGRAPHY, 40(4), 603-608, 2016
    Link to Paper Search Results by DOI
  18. Additional Value of Diffusion-weighted MRI to Gd-EOB-DTPA-enhanced Hepatic MRI for the Detection of liver Metastasis:the Difference Depending on the Experience of the Radiologists., Hiroshima Journal of Medical Sciences, 64, 15-21, 2015
  19. Diagnostic Performance of Positron Emission Tomography for the Presurgical Evaluation of Patients with Non-lesional Intractable Partial Epilepsy: Comparison among 18F-FDG, 11C-Flumazenil, and 11C-Flumazenil Binding Potential Imaging Using Statistical Imaging Analysis., Hiroshima Journal of Medical Sciences., 64, 51-57, 2015
  20. Coronary CT angiography in patients with implanted cardiac devices: initial experience with the metal artefact reduction technique, BRITISH JOURNAL OF RADIOLOGY, 89(1067), 2016
    Link to Paper Search Results by DOI
  21. Effects of Iterative Reconstruction Algorithms on Computer-assisted Detection (CAD) Software for Lung Nodules in Ultra-low-dose CT for Lung Cancer Screening, ACADEMIC RADIOLOGY, 24(2), 124-130, 201702
    Link to Paper Search Results by DOI
  22. Sarcopenia is closely associated with pancreatic exocrine insufficiency in patients with pancreatic disease, PANCREATOLOGY, 17(1), 70-75, 2017
    Link to Paper Search Results by DOI
  23. Aortic and Hepatic Contrast Enhancement During Hepatic-Arterial and Portal Venous Phase Computed Tomography Scanning: Multivariate Linear Regression Analysis Using Age, Sex, Total Body Weight, Height, and Cardiac Output, JOURNAL OF COMPUTER ASSISTED TOMOGRAPHY, 41(2), 309-314, 2017
    Link to Paper Search Results by DOI
  24. Lung cancer screening with ultra-low dose CT using full iterative reconstruction, JAPANESE JOURNAL OF RADIOLOGY, 35(4), 179-189, 201704
    Link to Paper Search Results by DOI
  25. Diffusion-weighted MR imaging of non-complicated hepatic cysts: Value of 3T computed diffusion-weighted imaging, EUROPEAN JOURNAL OF RADIOLOGY OPEN, 3, 138-144, 2016
    Link to Paper Search Results by DOI
  26. Paradoxical Effect of Cardiac Output on Arterial Enhancement at Computed Tomography: Does Cardiac Output Reduction Simply Result in an Increase in Aortic Peak Enhancement?, JOURNAL OF COMPUTER ASSISTED TOMOGRAPHY, 41(3), 349-353, 2017
    Link to Paper Search Results by DOI
  27. Functional image-guided stereotactic body radiation therapy planning for patients with hepatocellular carcinoma, MEDICAL DOSIMETRY, 42(2), 97-103, 2017
    Link to Paper Search Results by DOI
  28. Coronary Artery Stent Evalurtion with Modell-based lteratilve Reconstruction Coronary CT Angiography, ACADEMIC RADIOLOGY, 24(8), 975-981, 201708
    Link to Paper Search Results by DOI
  29. Hepatocellular carcinoma treated with sorafenib: Arterial tumor perfusion in dynamic contrast-enhanced CT as early imaging biomarkers for survival, EUROPEAN JOURNAL OF RADIOLOGY, 98, 41-49, 201801
    Link to Paper Search Results by DOI
  30. Accuracy of the raw-data-based effective atomic numbers and monochromatic CT numbers for contrast medium with a dual-energy CT technique, BRITISH JOURNAL OF RADIOLOGY, 91(1082), 2018
    Link to Paper Search Results by DOI
  31. Diagnostic accuracy of in-stent restenosis using model-based iterative reconstruction at coronary CT angiography: initial experience, BRITISH JOURNAL OF RADIOLOGY, 91(1082), 2018
    Link to Paper Search Results by DOI
  32. ★, Effect of contrast material injection duration on arterial enhancement at CT in patients with various cardiac indices: Analysis using computer simulation, PLOS ONE, 13(2), 20180223
    Link to Paper Search Results by DOI
  33. Effect of Patient Characteristics on Vessel Enhancement at Lower Extremity CT Angiography, KOREAN JOURNAL OF RADIOLOGY, 19(2), 265-271, 2018
    Link to Paper Search Results by DOI
  34. Quantification of the salivary volume flow rate in the parotid duct using the time-spatial labeling inversion pulse (Time-SLIP) technique at MRI: A feasibility study, JOURNAL OF MAGNETIC RESONANCE IMAGING, 47(4), 928-935, 201804
    Link to Paper Search Results by DOI
  35. Imaging features of papillary renal cell carcinoma with cystic change-dominant appearance in the era of the 2016 WHO classification, ABDOMINAL RADIOLOGY, 42(7), 1850-1856, 201707
    Link to Paper Search Results by DOI
  36. Preliminary Results of High-Precision Computed Diffusion Weighted Imaging for the Diagnosis of Hepatocellular Carcinoma at 3 Tesla, JOURNAL OF COMPUTER ASSISTED TOMOGRAPHY, 42(3), 373-379, 2018
    Link to Paper Search Results by DOI
  37. ★, Introduction to the Technical Aspects of Computed Diffusion-weighted Imaging for Radiologists, RADIOGRAPHICS, 38(4), 1131-1144, 2018
    Link to Paper Search Results by DOI
  38. Improved differentiation between high- and low-grade gliomas by combining dual-energy CT analysis and perfusion CT, MEDICINE, 97(32), 201808
    Link to Paper Search Results by DOI
  39. Automatic contrast medium extraction system using electron density data with dual-energy CT, BRITISH JOURNAL OF RADIOLOGY, 91(1090), 2018
    Link to Paper Search Results by DOI
  40. Development and Validation of Generalized Linear Regression Models to Predict Vessel Enhancement on Coronary CT Angiography, KOREAN JOURNAL OF RADIOLOGY, 19(6), 1021-1030, 2018
    Link to Paper Search Results by DOI
  41. Neointimal formation after carotid artery stenting: phantom and clinical evaluation of model-based iterative reconstruction (MBIR), EUROPEAN RADIOLOGY, 29(1), 161-167, 201901
    Link to Paper Search Results by DOI
  42. Improvement of image quality at CT and MRI using deep learning, JAPANESE JOURNAL OF RADIOLOGY, 37(1), 73-80, 201901
    Link to Paper Search Results by DOI
  43. Clinical application of radiation dose reduction at abdominal CT, EUROPEAN JOURNAL OF RADIOLOGY, 111, 68-75, 201902
    Link to Paper Search Results by DOI
  44. How to Improve the Conspicuity of Breast Tumors on Computed High b-value Diffusion-weighted Imaging, MAGNETIC RESONANCE IN MEDICAL SCIENCES, 18(2), 119-125, 2019
    Link to Paper Search Results by DOI
  45. Minimizing individual variations in arterial enhancement on coronary CT angiographs using "contrast enhancement optimizer": a prospective randomized single-center study, EUROPEAN RADIOLOGY, 29(6), 2998-3005, 201906
    Link to Paper Search Results by DOI
  46. Visualization of simulated small vessels on computed tomography using a model-based iterative reconstruction technique, DATA IN BRIEF, 13, 437-443, 201708
    Link to Paper Search Results by DOI
  47. Effect of Patient Characteristics on Vessel Enhancement in Pediatric Chest Computed Tomography Angiography, CANADIAN ASSOCIATION OF RADIOLOGISTS JOURNAL-JOURNAL DE L ASSOCIATION CANADIENNE DES RADIOLOGISTES, 70(2), 181-185, 201905
    Link to Paper Search Results by DOI
  48. Machine-learning integration of CT histogram analysis to evaluate the composition of atherosclerotic plaques: Validation with IB-IVUS, JOURNAL OF CARDIOVASCULAR COMPUTED TOMOGRAPHY, 13(2), 163-169, 2019
    Link to Paper Search Results by DOI
  49. Improving automatic contrast agent extraction system using monochromatic CT number, AUSTRALASIAN PHYSICAL & ENGINEERING SCIENCES IN MEDICINE, 42(3), 819-826, 201909
    Link to Paper Search Results by DOI
  50. Deep learning-based image restoration algorithm for coronary CT angiography, EUROPEAN RADIOLOGY, 29(10), 5322-5329, 201910
    Link to Paper Search Results by DOI
  51. Evaluation of raw-data-based and calculated electron density for contrast media with a dual-energy CT technique, REPORTS OF PRACTICAL ONCOLOGY AND RADIOTHERAPY, 24(5), 499-506, 2019
    Link to Paper Search Results by DOI
  52. Deep learning reconstruction improves image quality of abdominal ultra-high-resolution CT, EUROPEAN RADIOLOGY, 29(11), 6163-6171, 201911
    Link to Paper Search Results by DOI
  53. Clinical staging of upper urinary tract urothelial carcinoma for T staging: Review and pictorial essay, INTERNATIONAL JOURNAL OF UROLOGY, 26(11), 1024-1032, 201911
    Link to Paper Search Results by DOI
  54. ★, Deep Learning Reconstruction at CT: Phantom Study of the Image Characteristics, ACADEMIC RADIOLOGY, 27(1), 82-87, 202001
    Link to Paper Search Results by DOI
  55. Contrast enhancement on 100-and 120 kVp hepatic CT scans at thin adults in a retrospective cohort study Bayesian inference of the optimal enhancement probability, MEDICINE, 98(47), 201911
    Link to Paper Search Results by DOI
  56. Pseudo-random Trajectory Scanning Suppresses Motion Artifacts on Gadoxetic Acid-enhanced Hepatobiliary-phase Magnetic Resonance Images, MAGNETIC RESONANCE IN MEDICAL SCIENCES, 19(1), 21-28, 2020
    Link to Paper Search Results by DOI
  57. Deep Learning–based CT Image Reconstruction: Initial Evaluation Targeting Hypovascular Hepatic Metastases, Radiology: Artificial Intelligence, 1(6), 20191009
  58. Possibility of Deep Learning in Medical Imaging Focusing Improvement of Computed Tomography Image Quality, JOURNAL OF COMPUTER ASSISTED TOMOGRAPHY, 44(2), 161-167, 2020
    Link to Paper Search Results by DOI
  59. Individual Optimization of Contrast Media Injection Protocol at Hepatic Dynamic Computed Tomography Using Patient-Specific Contrast Enhancement Optimizer, JOURNAL OF COMPUTER ASSISTED TOMOGRAPHY, 44(2), 230-235, 2020
    Link to Paper Search Results by DOI
  60. Evaluation of metal artefact techniques with same contrast scale for different commercially available dual-energy computed tomography scanners, PHYSICAL AND ENGINEERING SCIENCES IN MEDICINE, 43(2), 539-546, 202006
    Link to Paper Search Results by DOI
  61. Deep learning reconstruction of drip-infusion cholangiography acquired with ultra-high-resolution computed tomography, ABDOMINAL RADIOLOGY, 45(9), 2698-2704, 202009
    Link to Paper Search Results by DOI
  62. Measurement of coronary artery calcium volume using ultra-high-resolution computed tomography: A preliminary phantom and cadaver study, EUROPEAN JOURNAL OF RADIOLOGY OPEN, 7, 2020
    Link to Paper Search Results by DOI
  63. A primer for understanding radiology articles about machine learning and deep learning, DIAGNOSTIC AND INTERVENTIONAL IMAGING, 101(12), 765-770, 202012
    Link to Paper Search Results by DOI
  64. Deep learning reconstruction of equilibrium phase CT images in obese patients, EUROPEAN JOURNAL OF RADIOLOGY, 133, 202012
    Link to Paper Search Results by DOI
  65. Prospective Memory Deficits in Multiple Sclerosis: Voxel-based Morphometry and Double Inversion Recovery Analysis, INTERNAL MEDICINE, 60(1), 39-46, 2021
    Link to Paper Search Results by DOI
  66. Computer Simulation of the Effects of Contrast Protocols on Aortic Signal Intensity on Magnetic Resonance Angiograms, CURRENT MEDICAL IMAGING, 17(3), 396-403, 2021
    Link to Paper Search Results by DOI
  67. Diagnostic value of deep learning reconstruction for radiation dose reduction at abdominal ultra-high-resolution CT, EUROPEAN RADIOLOGY, 31(7), 4700-4709, 202107
    Link to Paper Search Results by DOI
  68. Advanced CT techniques for assessing hepatocellular carcinoma, RADIOLOGIA MEDICA, 126(7), 925-935, 202107
    Link to Paper Search Results by DOI
  69. Tumor heterogeneity evaluated by computed tomography detects muscle-invasive upper tract urothelial carcinoma that is associated with inflammatory tumor microenvironment, SCIENTIFIC REPORTS, 11(1), 20210709
    Link to Paper Search Results by DOI
  70. Incidence and factor analysis of laryngohyoid fractures in hanging individuals-computed tomography study, EUROPEAN RADIOLOGY, 31(10), 7827-7833, 202110
    Link to Paper Search Results by DOI
  71. Accuracy of thin-slice model-based iterative reconstruction designed for brain CT to diagnose acute ischemic stroke in the middle cerebral artery territory: a multicenter study, NEURORADIOLOGY, 63(12), 2013-2021, 202112
    Link to Paper Search Results by DOI

Invited Lecture, Oral Presentation, Poster Presentation

  1. Reproduction of Color Vision Deficiency Considering Spectrum, Haruya Takahashi, Toru Higaki, Raytchev Bisser, Kazufumi Kaneda, International Workshop on Advanced Image Technology (IWAIT 2023), 2023/01/09, Without Invitation, English
  2. Acquiring Spectral Scattering Properties of Seawater from an RGB Image, Tomoya Wakasugi, Toru Higaki, Bisser Raytchev, Kazufumi Kaneda, Masashi Baba, International Workshop on Advanced Image Technology (IWAIT 2023), 2023/01/09, Without Invitation, English
  3. Semiquantitative evaluation of image quality of clinical CT images by radiologists: From physical evaluation of phantom to semiquantitative evaluation of clinical images, Kawashita I, Higaki T, Nakamura Y, Tatsugami F, Fukumoto W, Awai K, RSNA2022, 2022/11/27, Without Invitation, English
  4. Age estimation of cadavers using deep learning and postmortem CT images of the vertebral, Kawashita I, Fukumoto W, Higaki T, Mitani H, Chosa K, Awai K, RSNA2022, 2022/11/27, Without Invitation, English
  5. Importance of larger reconstruction matrix sizes for super-resolution deep Learning reconstruction, Higaki T, Tatsugami F, Nakamura Y, Kawashita I, Matsuura M, Awai K, RSNA2022, 2022/11/27, Without Invitation, English
  6. Utility of variable-rate contrast medium injection at computed tomography: A simulation study, Higaki T, Nakamura Y, Tatsugami F, Raytchev B, Kaneda K, Awai K, RSNA2022, 2022/11/27, Without Invitation, English
  7. Real-time volume rendering running on an AR device in medical applications., Kota Hashimoto, Toru Higaki, Raytchev Bisser Roumenov, Kazufumi Kaneda., International Workshop on Advanced Image Technology 2022 (IWAIT 2022), 2022/01/04, Without Invitation, English
  8. Multiple-Branch Deep Neural Network for Spectral Super-Resolution., Yuki Mikamoto, Masahiro Sakamoto, Toru Higaki, Bisser Raytchev, Kazufumi Kaneda., 28th International Workshop on Frontiers of Computer Vision (IW-FCV 2022), 2022/02/21, Without Invitation, Japanese
  9. Accuracy of CT number on virtual non-contrast enhanced images generated from stochastic material decomposition., Higaki T, Nakamura Y, Tatsugami F, Sueoka T, Fukumoto W, Awai K., RSNA2021, 2021/11/28, Without Invitation, English
  10. Physical characteristics of a new photon-counting detector CT: comparison of the spatial resolution with that on conventional energy-integrated detector CT scans., Higaki T, Kondo S, Teramoto F, Tsuchida R, Takahashi I, Yoshida R, Goto T, Nakamura Y, Awai K., RSNA2021, 2021/11/28, Without Invitation, English
  11. Measurement of directional task-based modulation transfer function at abdominal CT: a phantom study., Higaki T, Yokomachi K, Fujioka C, Nishimaru E, Nakamura Y, Awai K., RSNA2021, 2021/11/28, Without Invitation, English
  12. Physical characteristics of a new photon-counting detector CT scanner: comparison of the contrast-to-noise ratio and the noise power spectrum with those on conventional energy-integrated detector CT., Higaki T, Kondo S, Yokoi K, Kojima S, Takahashi I, Aoki Y, Watanabe F, Nakamura Y, Awai K., RSNA2021, 2021/11/28, Without Invitation, English
  13. Super-resolution deep learning reconstruction at CT: a phantom study for coronary CT angiography., Higaki T, Tatsugami F, Matsuura M, Taguchi H, Tsushima S, Nakamura Y, Awai K., RSNA2021, 2021/11/28, Without Invitation, English
  14. Various applications of deep learning-based reconstruction at CT: denoise, dual-energy CT, and super-resolution., Higaki T, Nakamura Y, Tatsugami F, Sueoka T, Tsushima S, Taguchi H, Matsuura M, Awai K., RSNA2021, 2021/11/28, Without Invitation, English
  15. Deep learning based spectral CT imaging for quantifying contrast medium enhancement and washout in hepatocellular carcinomas: comparison of iodine maps and virtual monochromatic images., Narita K, Nakamura Y, Higaki T, Kondo S, Honda Y, Kawashita I, Awai K., RSNA2021, 2021/11/28, Without Invitation, English
  16. Easy introduction of the photon counting detector CT (PCD-CT) for radiologists., Kondo S, Higaki T, Nakamura Y, Takahashi I, Goto T, Awai K., RSNA2021, 2021/11/28, Without Invitation, English
  17. A new MRI technique for the detailed inspection of compact bone: phantom and preliminary clinical study, Sueoka T, Kawashita I, Higaki T, Honda Y, Nishihara T, Tatsugami F, Nakamura Y, Awai K., RSNA2021, 2021/11/28, Without Invitation, English
  18. Improvement of spatial resolution by using super-resolution deep learning reconstruction at coronary CT angiography., Tatsugami F, Higaki T, Matsuura M, Taguchi H, Tsushima S, Awai K., RSNA2021, 2021/11/28, Without Invitation, English
  19. Radiation dose reduction at abdominal ultra-high-resolution CT with deep learning reconstruction., Narita K, Nakamura Y, Higaki T, Akagi M, Honda Y, Awai K, et al., RSNA2020, 2020/11/29, Without Invitation, English
  20. Utility of deep learning reconstruction of equilibrium phase images in obese patients., Akagi M, Nakamura Y, Narita K, Honda Y, Higaki T, Awai K, et al., RSNA2020, 2020/11/29, Without Invitation, English
  21. Utility of iterative noise reduction for gadoxetic acid-enhanced hepatobiliary-phase magnetic resonance imaging., Narita K, Nakamura Y, Higaki T, Nishihara T, Bito Y, Awai K, et al., RSNA2020, 2020/11/29, Without Invitation, English
  22. Image characteristics of deep-learning-based rapid kV switching dual energy CT scans: A phantom study., Higaki T, Nakamura Y, Tatsugami F, Sueoka T, Fujioka C, Awai K, et al., RSNA2020, 2020/11/29, Without Invitation, English
  23. Maximization of the diagnostic ability of ultra-high-resolution CT: optimal scan parameters and image reconstruction techniques., Higaki T, Nakamura Y, Akagi M, Fukumot W, Tatsugami F, Awai K., RSNA2020, 2020/11/29, Without Invitation, English
  24. Contrast enhancement protocol at CT: basics and advanced optimization using computer simulation., Higaki T, Matsumot Y, Tatsugami F, Nakamura Y, Fukumoto W, Awai K., RSNA2020, 2020/11/29, Without Invitation, English
  25. The usefulness of low dose- and 4-dimensional CT imaging using a deep learning reconstruction., Tatsugami F, Higaki T, Mitani H, Sueoka T, Fujioka C, Awai K, et al., RSNA2020, 2020/11/29, Without Invitation, English
  26. Basic physical information for radiologists wishing to fully utilize the capability of dual-energy CT., Higaki T, Nakamura Y, Tatsugami F, Sueoka T, Honda Y, Awai K, et al., RSNA2020, 2020/11/29, Without Invitation, English
  27. The clinical evaluation of the upper urinary tract cancer: what radiologists should know., Honda Y, Nakamura Y, Akagi M, Narita K, Higaki T, Awai K, et al., RSNA2020, 2020/11/29, Without Invitation, English
  28. Abdominal deep leaning spectral imaging: image quality of virtual monochromatic images in the equilibrium phase, Nakamura Y, Higaki T, Akagi M, Narita K, Honda Y, Taguchi H, Tsushima S, Awai K., ECR2020, 2020/07/15, Without Invitation, English
  29. Improvement of image quality by using deep learning image reconstruction at coronary CT angiography performed with high-definition scan mode., Tatsugami F, Higaki T, Fukumoto W, Nakamura Y, Fujioka C, Iida M, Awai K, ECR2020, 2020/07/15, Without Invitation, English
  30. Radiation dose optimization using automatic exposure control at rapid kV-switching dual-energy CT with deep learning technology: Feasibility study using a phantom, Higaki T, Nakamura Y, Tatsugami F, Honda Y, Fujioka C, Awai K, ECR2020, 2020/07/15, Without Invitation, English
  31. Utility of framework software to support medical image processing, Higaki T, Tatsugami F, Nakamura Y, Kaichi Y, Itada Y, Awai K, ECR2020, 2020/07/15, Without Invitation, English
  32. Radiation dose reduction for coronary CT angiography using deep learning reconstruction: A phantom study, Higaki T, Tatsugami F, Nakamura Y, Fukumoto W, Fujioka C, Awai K, ECR2020, 2020/07/15, Without Invitation, English
  33. Dual-energy CT of the renal lesions, Mori T, Honda Y, Higaki T, Fujioka C, Nakamura Y, Terada H, Akagi M, Awai K, RSNA2019, 2019/12/01, Without Invitation, English
  34. Comparison of emphysema scores on low and ultra-low radiation dose CT images using different reconstruction methods, Fukumoto W, Schreuder A, Lafebre S J, Higaki T, Prokop M, Nakamura Y, Awai K, RSNA2019, 2019/12/01, Without Invitation, English
  35. CT image retrieval based on morphological similarities in diffuse lung diseases using a deep convolutional neural network, Terada H, Higaki T, Takebe H, Moriwaki Y, Baba T, Awai K, RSNA2019, 2019/12/01, Without Invitation, English
  36. Capability of a new model-based Iterative reconstruction for brain CT to diagnose acute ischemic stroke: multicenter study, Mitani H, Tatsugami F, Higaki T, Prokop M, Ono C, Ono K, Fukumoto W, Nakamura Y, Awai K, RSNA2019, 2019/12/01, Without Invitation, English
  37. Estimation of minimal liver fibrosis using gadoxetic acid-enhanced liver MRI and machine learning, Narita K, Nakamura Y, Akagi M, Higaki T, Iida M, Awai K, RSNA2019, 2019/12/01, Without Invitation, English
  38. Radiation dose reduction in chest CT at a Micro-Dose (mD) level by noise simulation and noise-specific anatomic Neural Network Convolution (NNC) Deep-Learning (DL) with k-means clustering, Zhao Y, Zarshenas A, Higaki T, Suzuki K, Awai K, RSNA2019, 2019/12/01, Without Invitation, English
  39. CT imaging of fetal skeletal anomalies at minimized radiation exposure: clinical significance, indications, and scan protocol, Matsubara Y, Tani C, Higaki T, Nakamura Y, Honda Y, Fukumoto W, Sakane H, Awai K, RSNA2019, 2019/12/01, Without Invitation, English
  40. A Projection Mapping System onto a Human Body for Medical Applications., Fukuhara R, Kaneda K, Tamaki T, Raytchev B, Higaki T, Nishimoto S, Sotsuka Y., Eurographics 2019, 2019/05/06, Without Invitation, English
  41. Image Noise Reduction with Deep Learning-Based CT Image Reconstruction., Higaki T, Nakamura Y, Tatsugami F, Akino N, Awai K., ECR2019, 2019/02/27, Without Invitation, English
  42. Feasibility of radiation dose reduction using a deep learning based reconstruction at coronary CT angiography., Tatsugami F, Higaki T, Yuko Nakamura, Fukumoto W, Yuya Ito, So Tsushima, Awai K., ECR2019, 2019/02/27, Without Invitation, English
  43. Radiation dose reduction in calcium volume measurement at cardiac CT using model-based iterative reconstruction: A phantom study., Tatsugami F, Higaki T, Nakamura Y, Iida M, Fujioka C, Awai K., ECR2019, 2019/02/27, Without Invitation, English
  44. Deep learning based reconstruction improves the image quality of abdominal ultra-high-resolution computed tomography scans., Utsunomiya K, Nakamura Y, Higaki T, Akagi M, Narita K, Zhou J, Yu Z, Akino N, Awai K., ECR2019, 2019/02/27, Without Invitation, English
  45. Measurement of coronary artery calcium score using ultra-high resolution CT: Cadaver study., Fukumoto W, Higaki T, Tatsugami F, Klein MM, Prokop MM, Awai K., ECR2019, 2019/02/27, Without Invitation, English
  46. 3 Tesla magnetic resonance imaging: Clinical capability of new applications for abdominal imaging., Nakamura Y, Higaki T, Nishihara T, Harada K, Takizawa M, Bito Y, Narita K, Akagi M, Awai K., ECR2019, 2019/02/27, Without Invitation, English
  47. Pseudo-random trajectory scan technique to suppress motion artifacts on gadoxetic acid-enhanced hepatobiliary-phase magnetic resonance images., Nakamura Y, Higaki T, Nishihara T, Harada K, Takizawa M, Bito Y, Narita K, Akagi M, Awai K., ECR2019, 2019/02/27, Without Invitation, English
  48. Dual-Energy Computed Tomography of Renal Lesions., Honda Y, Terada H, Higaki T, Fujioka C, Nakamura Y, Awai K., ECR2019, 2019/02/27, Without Invitation, English
  49. Similar CT image retrieval method based on lesion nature and their three-dimensional distribution., Yasutaka Moriwaki, Nobuhiro Miyazaki, Hiroaki Takebe, Takayuki Baba, Hiroaki Terada, Toru Higaki, Kazuo Awai, Machiko Nakagawa, Akio Ozawa, Kennji Kitayama, Yasuharu Ogino., SPIE Medical Imaging 2019, 2019/02/16, Without Invitation, English
  50. Improvement of diagnostic image quality of abdominal CT by using a deep-learning based reconstruction: Initial clinical trial targeting hypervascular hepatocellular carcinoma., Nakamura Y, Higaki T, Yu Z, Zhou J, Akino N, Awai K, et al., RSNA2018., 2018/11/25, Without Invitation, English
  51. Demonstration of the fetal bone cortex on MRI Scans: Preliminary clinical study on normal fetal specimens., Matsubara Y, Tani C, Higaki T, Kamioka S, Nakamura Y, Awai K., RSNA2018., 2018/11/25, Without Invitation, English
  52. CT findings on hepatocellular carcinoma in patients with hepatitis C showing a sustained virologic response after interferon-free therapy: Comparison with that in patients with interferon-based therapy., Akagi M, Nakamura Y, Narita K, Honda Y, Higaki T, Awai K, et al., RSNA2018., 2018/11/25, Without Invitation, English
  53. Effect of simulated micro-dose (mD) CT on the performance of neural network convolution (NNC) deep-learning (DL) in radiation dose reduction in chest CT., Zhao Y, Zarshenas A, Higaki T, Awai K, Suzuki K., RSNA2018., 2018/11/25, Without Invitation, English
  54. Development a software which assists radiologists to determine optimal contrast material administration protocol at CT: Validation study using a computer simulation., Higaki T, Matsumoto Y , Masuda T, Nakamura Y, Tatsugami F, Awai K., RSNA2018., 2018/11/25, Without Invitation, English
  55. Accuracy of volume measurements of coronary calcification at CT using model-based iterative reconstruction: a phantom study., Higaki T, Tatsugami T, Fujioka C, Yokomachi K, Nakamura Y, Awai K., RSNA2018., 2018/11/25, Without Invitation, English
  56. Imaging Physiology of Contrast Agent: Difference in Pharmacokinetic and Signal Characteristics Between Gadolinium and Iodine Contrast Agent., Higaki T, Nakamura Y, Tatsugami F, Honda Y, Usuki R, Awai K., RSNA2018., 2018/11/25, Without Invitation, English
  57. Easy Understanding of Theory and Image Characteristics of the Model-Based Iterative Reconstruction at CT for Radiologists: How Does It Work?, Higaki T, F Tatsugami, Nakamura Y, Maeda S, Tsushima S, Awai K., RSNA2018., 2018/11/25, Without Invitation, English
  58. "Virtual" High-Dose Technology: Radiation Dose Reduction in Thin-Slice Chest CT at a Micro-Dose (mD) Level by Means of 3D Deep Neural Network Convolution (NNC)., Zarshenas A, Zhao Y, Liu J, Higaki T, Awai K, Suzuki K., RSNA2018., 2018/11/25, Without Invitation, English
  59. Possibility of Deep Learning Technique in Medical Imaging: Can Deep Learning Improve Image Quality?, Nakamura Yuko, Higaki T, Yu Z, Zhou J, Akino N; Awai K., RSNA2018., 2018/11/25, Without Invitation, English
  60. Non-Invasive Evaluation of Liver Fibrosis Using Imaging Technique: Current Problems and Future Perspective., Narita K, Nakamura Y, Higaki T, Akagi M, Iida M, Awai K., RSNA2018., 2018/11/25, Without Invitation, English
  61. Update of CT Urography: Current Techniques, Clinical Utility, and New Applications., Honda Y, Nakamura Y, Terada H, Higaki T, Fujioka C, Awai K., RSNA2018., 2018/11/25, Without Invitation, English
  62. Deep 3D Anatomy-Specific Neural Network Convolution for Radiation Dose Reduction in Chest CT at a Micro-Dose Level., Amin Zarshenas, Yuji Zhao, Junchi Liu, Toru Higaki, Wataru Fukumoto, Kazuo Awai, Kenji Suzuki., EMBC2018: 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society., 2018/07/17, Without Invitation, English
  63. Improvement of diagnostic image quality of abdominal CT by using a deep learning based reconstruction: Initial clinical trial targeting hepatic metastases., Nakamura Y, Higaki T, Tatsugami F, Zhou J, Yu Z, Akino N, Ito Y, Iida M, Awai K., ECR2018, 2018/02/28, Without Invitation, English
  64. Improving image quality of low-dose abdominal CT by a deep learning reconstruction: Feasibility study using a liver phantom including simulated tumors., Nakamura Y, Higaki T, Tatsugami F, Zhou J, Yu Z, Akino N, Nemoto T, Iida M, Awai K., ECR2018, 2018/02/28, Without Invitation, English
  65. Possibility of deep learning technique in CT image reconstruction., Higaki T, Nakamura Y, Tatsugami F, Iida M, Yu Z, Zhou J, Akino N, Tsushima S, Awai K., ECR2018, 2018/02/28, Without Invitation, English
  66. Radiation dose reduction in CT using Deep Learning based Reconstruction (DLR): A phantom study., Higaki T, Nishimaru E, Nakamura Y, Tatsugami F, Yu Z, Zhou J, Verleker AP, Akino N, Awai K., ECR2018, 2018/02/28, Without Invitation, English
  67. Essential Knowledge About Gadolinium Contrast Agents on Magnetic Resonance Imaging to Plan Optimal Contrast Enhancement Protocols: Graphic Demonstration Using a Computer Simulation., Higaki T, Nakamura Y, Tatsugami F, Honda Y, Akiyama Y, Awai K., RSNA2017, 2017/11/26, Without Invitation, English
  68. A new quantitative index for the noise power spectrum at CT: Correlation with subjective nodule detectability on CT images., Higaki T, Tstsugami F, Nakamura Y, Fujioka C, Tsushima S, Awai K, et al., RSNA2017, 2017/11/26, Without Invitation, English
  69. Improvement of Spatial Resolution of CT Using Model-Based Iterative Reconstruction on CT: A Phantom Study., Higaki T, Tatsugami F, Nakamura Y, Yokomachi K, Tsushima S, Awai K, et al., 2017/11/26, Without Invitation, English
  70. Novel Technique to Generate Computed Diffusion Weighted Brain MRI with Ultra-High B-Values., Higaki T, Tatsugami F, Kaichi Y, Akiyama Y, Umeda M, Awai K., RSNA2017, 2017/11/26, Without Invitation, English
  71. The Detectability of Forward Projected Model-Based Iterative Reconstruction for Low Contrast Lesions: Acute Cerebral Infarction-Phantom Study., Higaki T, Kaichi Y, Tatsugami F, Taguchi H, Iida M, Awai K., RSNA2017, 2017/11/26, Without Invitation, English
  72. Easy understanding of the technical aspects of computed diffusion-weighted Image (cDWI) for radiologis, Higaki T, Nakamura Y, Sakane H, Fukumoto W, Kassai Y, Awai K, RSNA 2016, 2016/11/27, Without Invitation, English, RSNA, Chicago
  73. Contrast material injection protocols at coronary CT angiorapraphy with short injection duration can yield sufficient arterial enhancement in wide range of cardiac output value: computer simulation study., Higaki T, Nakaura T, Kidoh M, Yuki H, Yamashita Y, Awai K, RSNA 2016, 2016/11/27, Without Invitation, English, RSNA, Chicago
  74. Simulation technique for predicting organ enhancement, Toru Higaki, Kazuo Awai, User seminar by Nemoto Kyorindo, RSNA 2015: 100th Scientific assembly and annual meeting., 2015/11/30, With Invitation, English, Chicago, IL, USA
  75. Easy understanding of the technical aspects of abdominal perfusion CT for radiologists., Higaki T, Nakamura Y, Fukumoto W, Kiguchi M, Iida M, Awai K, Honda Y., RSNA 2015, 2015/11/29, Without Invitation, English
  76. Improved accuracy of the CT number of iodine-enhanced structures on virtual monochromatic dual-energy CT images., Higaki T, Kaichi Y, Kiguchi M, Tatsugami F, Tsushima S, Awai K, Iida M, Honda Y., RSNA 2015, 2015/11/29, Without Invitation, English
  77. Computer simulation of contrast enhancement in the whole body: a highly accurate simulation of the bolus transmission of contrast material in individual organs., Higaki T,Nakamura Y, Tatsugami F, Kiguchi M, Iida M, Awai K., RSNA 2015, 2015/11/29, Without Invitation, English
  78. Technique for the composition of virtual monochromatic images in the fourier domain: high contrast-to-noise on CT images of brain tumors., Higaki T, Kaichi Y, Fukumoto W, Honda Y, Iida M, Awai K., RSNA 2015, 2015/11/29, Without Invitation, English
  79. Techniques to genetate high-accuraey computed diffusion- weighted images(cDWI)of the liver., Higaki T, Nakamura Y, Akiyama Y, Ohkubo T, Kassai Y, Awai K., RSNA 2015, 2015/11/29, Without Invitation, English
  80. Registration Method for Gadoxetate Disodium-enhanced MR and Radiation Dose Distribution Maps using an Extracted Liver-region Mask, Toru Higaki, Kazuo Awai, et al., RSNA 2014: 100th Scientific assembly and annual meeting, 2014/11/30, Without Invitation, English
  81. Measurement of Electron Density Using Raw data-based Dual-energy Computed Tomography: Phantom Study, Toru Higaki, Kazuo Awai, et al., RSNA 2014: 100th Scientific assembly and annual meeting, 2014/11/30, Without Invitation, English
  82. Utility of radial scan for identification of arterial hypervascularity of hepatocellular carcinoma on gadoxetic acid-enhanced MR images, Nakamura Y, Higaki T, Narita K, Akagi M, Matsubara Y, Nishihara T, Harada K, Takizawa M, Shirase R, Bito Y, Iida M, Awai K, ECR2020, Without Invitation, English

Awards

  1. 2017/02/27, Certificate of Merit,, European Society of Radiology (ESR),, Radiation dose reduction in CT using Deep Learning based Reconstruction (DLR): A phantom study
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  2. 2018/11/30, Certificate of Merit,, Radiological Society of North America,, Easy Understanding of Theory and Image Characteristics of the Model-Based Iterative Reconstruction at CT for Radiologists: How Does It Work?

External Funds

Acceptance Results of Competitive Funds

  1. Adaptable and Seamless Technology transfer Program through targetdriven R&D, 2012/11/01, 2013/10/31
  2. KAKENHI, 2013, 2015
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  3. KAKENHI, 2016, 2018
  4. KAKENHI(Grant-in-Aid for Scientific Research (C)), 2020, 2022