Updated on 2024/03/02

写真a

 
TAKITA HIROTAKA
 
Organization
Graduate School of Medicine Department of Clinical Medical Science Lecturer
School of Medicine Department of Medical Science
Title
Lecturer
Affiliation
Institute of Medicine

Position

  • Graduate School of Medicine Department of Clinical Medical Science 

    Lecturer  2023.04 - Now

  • School of Medicine Department of Medical Science 

    Lecturer  2023.04 - Now

Degree

  • 博士(医学) ( Osaka City University )

  • 学士(医学) ( Osaka City University )

Research Areas

  • Life Science / Radiological sciences  / 人工知能

Research Interests

  • 放射線

  • 医用画像

  • 人工知能

  • Deep Learning

Professional Memberships

  • 神経放射線学会

    2019.10 - Now

  • 日本医学放射線学会

    2016.04 - Now

Awards

  • 第36回最優秀論文賞

    Hirotaka Takita

    2024.04   AI-based Virtual Synthesis of Methionine PET from Contrast-enhanced MRI: Development and External Validation Study.

  • 令和5年度医学部長賞優秀賞

    Hirotaka Takita

    2024.03   AI-based Virtual Synthesis of Methionine PET from Contrast-enhanced MRI: Development and External Validation Study.

  • Kato Prize

    Hirotaka Takita

    2024.02   AI-based Virtual Synthesis of Methionine PET from Contrast-enhanced MRI: Development and External Validation Study.

  • 優秀会長賞

    田北大昂

    2020.04   日本医学放射線学会   DWI scoring system for prognosis of acute encephalopathy with biphasic seizures and late reduced restriction

Papers

  • Evaluation of cranial nerve involvement in chordomas and chondrosarcomas: a retrospective imaging study

    Tatsushi Oura, Taro Shimono, Daisuke Horiuchi, Takeo Goto, Hirotaka Takita, Taro Tsukamoto, Hiroyuki Tatekawa, Daiju Ueda, Shu Matsushita, Yasuhito Mitsuyama, Natsuko Atsukawa, Yukio Miki

    Neuroradiology   2024.02( ISSN:0028-3940

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    Publishing type:Research paper (scientific journal)  

    DOI: 10.1007/s00234-024-03322-1

    PubMed

  • Deep learning-based diffusion tensor image generation model: a proof-of-concept study.

    Hiroyuki Tatekawa, Daiju Ueda, Hirotaka Takita, Toshimasa Matsumoto, Shannon L Walston, Yasuhito Mitsuyama, Daisuke Horiuchi, Shu Matsushita, Tatsushi Oura, Yuichiro Tomita, Taro Tsukamoto, Taro Shimono, Yukio Miki

    Scientific reports   14 ( 1 )   2911 - 2911   2024.02

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    Publishing type:Research paper (scientific journal)   International / domestic magazine:International journal  

    This study created an image-to-image translation model that synthesizes diffusion tensor images (DTI) from conventional diffusion weighted images, and validated the similarities between the original and synthetic DTI. Thirty-two healthy volunteers were prospectively recruited. DTI and DWI were obtained with six and three directions of the motion probing gradient (MPG), respectively. The identical imaging plane was paired for the image-to-image translation model that synthesized one direction of the MPG from DWI. This process was repeated six times in the respective MPG directions. Regions of interest (ROIs) in the lentiform nucleus, thalamus, posterior limb of the internal capsule, posterior thalamic radiation, and splenium of the corpus callosum were created and applied to maps derived from the original and synthetic DTI. The mean values and signal-to-noise ratio (SNR) of the original and synthetic maps for each ROI were compared. The Bland-Altman plot between the original and synthetic data was evaluated. Although the test dataset showed a larger standard deviation of all values and lower SNR in the synthetic data than in the original data, the Bland-Altman plots showed each plot localizing in a similar distribution. Synthetic DTI could be generated from conventional DWI with an image-to-image translation model.

    DOI: 10.1038/s41598-024-53278-8

    PubMed

  • Diagnostic Performance of Generative AI and Physicians: A Systematic Review and Meta-Analysis

    Hirotaka Takita, Shannon L Walston, Hiroyuki Tatekawa, Kenichi Saito, Yasushi Tsujimoto, Yukio Miki, Daiju Ueda

    2024.01

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  • Comparison of the diagnostic accuracy among GPT-4 based ChatGPT, GPT-4V based ChatGPT, and radiologists in musculoskeletal radiology

    Daisuke Horiuchi, Hiroyuki Tatekawa, Tatsushi Oura, Taro Shimono, Shannon L Walston, Hirotaka Takita, Shu Matsushita, Yasuhito Mitsuyama, Yukio Miki, Daiju Ueda

    2023.12

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    Abstract

    Objective

    To compare the diagnostic accuracy of Generative Pre-trained Transformer (GPT)-4 based ChatGPT, GPT-4 with vision (GPT-4V) based ChatGPT, and radiologists in musculoskeletal radiology.

    Materials and Methods

    We included 106 “Test Yourself” cases fromSkeletal Radiologybetween January 2014 and September 2023. We input the medical history and imaging findings into GPT-4 based ChatGPT and the medical history and images into GPT-4V based ChatGPT, then both generated a diagnosis for each case. Two radiologists (a radiology resident and a board-certified radiologist) independently provided diagnoses for all cases. The diagnostic accuracy rates were determined based on the published ground truth. Chi-square tests were performed to compare the diagnostic accuracy of GPT-4 based ChatGPT, GPT-4V based ChatGPT, and radiologists.

    Results

    GPT-4 based ChatGPT significantly outperformed GPT-4V based ChatGPT (p< 0.001) with accuracy rates of 43% (46/106) and 8% (9/106), respectively. The radiology resident and the board-certified radiologist achieved accuracy rates of 41% (43/106) and 53% (56/106). The diagnostic accuracy of GPT-4 based ChatGPT was comparable to that of the radiology resident but was lower than that of the board-certified radiologist, although the differences were not significant (p= 0.78 and 0.22, respectively). The diagnostic accuracy of GPT-4V based ChatGPT was significantly lower than those of both radiologists (p< 0.001 and < 0.001, respectively).

    Conclusion

    GPT-4 based ChatGPT demonstrated significantly higher diagnostic accuracy than GPT-4V based ChatGPT. While GPT-4 based ChatGPT’s diagnostic performance was comparable to radiology residents, it did not reach the performance level of board-certified radiologists in musculoskeletal radiology.

    DOI: 10.1101/2023.12.07.23299707

  • Accuracy of ChatGPT generated diagnosis from patient's medical history and imaging findings in neuroradiology cases. Reviewed

    Daisuke Horiuchi, Hiroyuki Tatekawa, Taro Shimono, Shannon L Walston, Hirotaka Takita, Shu Matsushita, Tatsushi Oura, Yasuhito Mitsuyama, Yukio Miki, Daiju Ueda

    Neuroradiology   66 ( 1 )   73 - 79   2023.11( ISSN:00283940

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    Publishing type:Research paper (scientific journal)   International / domestic magazine:International journal  

    PURPOSE: The noteworthy performance of Chat Generative Pre-trained Transformer (ChatGPT), an artificial intelligence text generation model based on the GPT-4 architecture, has been demonstrated in various fields; however, its potential applications in neuroradiology remain unexplored. This study aimed to evaluate the diagnostic performance of GPT-4 based ChatGPT in neuroradiology. METHODS: We collected 100 consecutive "Case of the Week" cases from the American Journal of Neuroradiology between October 2021 and September 2023. ChatGPT generated a diagnosis from patient's medical history and imaging findings for each case. Then the diagnostic accuracy rate was determined using the published ground truth. Each case was categorized by anatomical location (brain, spine, and head & neck), and brain cases were further divided into central nervous system (CNS) tumor and non-CNS tumor groups. Fisher's exact test was conducted to compare the accuracy rates among the three anatomical locations, as well as between the CNS tumor and non-CNS tumor groups. RESULTS: ChatGPT achieved a diagnostic accuracy rate of 50% (50/100 cases). There were no significant differences between the accuracy rates of the three anatomical locations (p = 0.89). The accuracy rate was significantly lower for the CNS tumor group compared to the non-CNS tumor group in the brain cases (16% [3/19] vs. 62% [36/58], p < 0.001). CONCLUSION: This study demonstrated the diagnostic performance of ChatGPT in neuroradiology. ChatGPT's diagnostic accuracy varied depending on disease etiologies, and its diagnostic accuracy was significantly lower in CNS tumors compared to non-CNS tumors.

    DOI: 10.1007/s00234-023-03252-4

    PubMed

  • Comparative Analysis of ChatGPT’s Diagnostic Performance with Radiologists Using Real-World Radiology Reports of Brain Tumors

    Yasuhito Mitsuyama, Hiroyuki Tatekawa, Hirotaka Takita, Fumi Sasaki, Akane Tashiro, Satoshi Oue, Shannon L Walston, Yukio Miki, Daiju Ueda

    2023.10

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    Abstract

    Background

    Large Language Models like Chat Generative Pre-trained Transformer (ChatGPT) have demonstrated potential for differential diagnosis in radiology. Previous studies investigating this potential primarily utilized quizzes from academic journals, which may not accurately represent real-world clinical scenarios.

    Purpose

    This study aimed to assess the diagnostic capabilities of ChatGPT using actual clinical radiology reports of brain tumors and compare its performance with that of neuroradiologists and general radiologists.

    Methods

    We consecutively collected brain MRI reports from preoperative brain tumor patients at Osaka Metropolitan University Hospital, taken from January to December 2021. ChatGPT and five radiologists were presented with the same findings from the reports and asked to suggest differential and final diagnoses. The pathological diagnosis of the excised tumor served as the ground truth. Chi-square tests and Fisher’s exact test were used for statistical analysis.

    Results

    In a study analyzing 99 radiological reports, ChatGPT achieved a final diagnostic accuracy of 75% (95% CI: 66, 83%), while radiologists’ accuracy ranged from 64% to 82%. ChatGPT’s final diagnostic accuracy using reports from neuroradiologists was higher at 82% (95% CI: 71, 89%), compared to 52% (95% CI: 33, 71%) using those from general radiologists with a p-value of 0.012. In the realm of differential diagnoses, ChatGPT’s accuracy was 95% (95% CI: 91, 99%), while radiologists’ fell between 74% and 88%. Notably, for these differential diagnoses, ChatGPT’s accuracy remained consistent whether reports were from neuroradiologists (96%, 95% CI: 89, 99%) or general radiologists (91%, 95% CI: 73, 98%) with a p-value of 0.33.

    Conclusion

    ChatGPT exhibited good diagnostic capability, comparable to neuroradiologists in differentiating brain tumors from MRI reports. ChatGPT can be a second opinion for neuroradiologists on final diagnoses and a guidance tool for general radiologists and residents, especially for understanding diagnostic cues and handling challenging cases.

    Summary

    This study evaluated ChatGPT’s diagnostic capabilities using real-world clinical MRI reports from brain tumor cases, revealing that its accuracy in interpreting brain tumors from MRI findings is competitive with radiologists.

    Key results

    ChatGPT demonstrated a diagnostic accuracy rate of 75% for final diagnoses based on preoperative MRI findings from 99 brain tumor cases, competing favorably with five radiologists whose accuracies ranged between 64% and 82%. For differential diagnoses, ChatGPT achieved a remarkable 95% accuracy, outperforming several of the radiologists.

    Radiology reports from neuroradiologists and general radiologists showed varying accuracy when input into ChatGPT. Reports from neuroradiologists resulted in higher diagnostic accuracy for final diagnoses, while there was no difference in accuracy for differential diagnoses between neuroradiologists and general radiologists.

    DOI: 10.1101/2023.10.27.23297585

  • Comparison of the Diagnostic Performance from Patient’s Medical History and Imaging Findings between GPT-4 based ChatGPT and Radiologists in Challenging Neuroradiology Cases

    Daisuke Horiuchi, Hiroyuki Tatekawa, Tatsushi Oura, Satoshi Oue, Shannon L Walston, Hirotaka Takita, Shu Matsushita, Yasuhito Mitsuyama, Taro Shimono, Yukio Miki, Daiju Ueda

    2023.08

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    Abstract

    Purpose

    To compare the diagnostic performance between Chat Generative Pre-trained Transformer (ChatGPT), based on the GPT-4 architecture, and radiologists from patient’s medical history and imaging findings in challenging neuroradiology cases.

    Methods

    We collected 30 consecutive “Freiburg Neuropathology Case Conference” cases from the journal Clinical Neuroradiology between March 2016 and June 2023. GPT-4 based ChatGPT generated diagnoses from the patient’s provided medical history and imaging findings for each case, and the diagnostic accuracy rate was determined based on the published ground truth. Three radiologists with different levels of experience (2, 4, and 7 years of experience, respectively) independently reviewed all the cases based on the patient’s provided medical history and imaging findings, and the diagnostic accuracy rates were evaluated. The Chi-square tests were performed to compare the diagnostic accuracy rates between ChatGPT and each radiologist.

    Results

    ChatGPT achieved an accuracy rate of 23% (7/30 cases). Radiologists achieved the following accuracy rates: a junior radiology resident had 27% (8/30) accuracy, a senior radiology resident had 30% (9/30) accuracy, and a board-certified radiologist had 47% (14/30) accuracy. ChatGPT’s diagnostic accuracy rate was lower than that of each radiologist, although the difference was not significant (p= 0.99, 0.77, and 0.10, respectively).

    Conclusion

    The diagnostic performance of GPT-4 based ChatGPT did not reach the performance level of either junior/senior radiology residents or board-certified radiologists in challenging neuroradiology cases. While ChatGPT holds great promise in the field of neuroradiology, radiologists should be aware of its current performance and limitations for optimal utilization.

    DOI: 10.1101/2023.08.28.23294607

  • AI-based Virtual Synthesis of Methionine PET from Contrast-enhanced MRI: Development and External Validation Study. Reviewed

    Hirotaka Takita, Toshimasa Matsumoto, Hiroyuki Tatekawa, Yutaka Katayama, Kosuke Nakajo, Takehiro Uda, Yasuhito Mitsuyama, Shannon L Walston, Yukio Miki, Daiju Ueda

    Radiology   308 ( 2 )   e223016   2023.08( ISSN:00338419

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    Authorship:Lead author   Publishing type:Research paper (scientific journal)   International / domestic magazine:International journal  

    Background Carbon 11 (11C)-methionine is a useful PET radiotracer for the management of patients with glioma, but radiation exposure and lack of molecular imaging facilities limit its use. Purpose To generate synthetic methionine PET images from contrast-enhanced (CE) MRI through an artificial intelligence (AI)-based image-to-image translation model and to compare its performance for grading and prognosis of gliomas with that of real PET. Materials and Methods An AI-based model to generate synthetic methionine PET images from CE MRI was developed and validated from patients who underwent both methionine PET and CE MRI at a university hospital from January 2007 to December 2018 (institutional data set). Pearson correlation coefficients for the maximum and mean tumor to background ratio (TBRmax and TBRmean, respectively) of methionine uptake and the lesion volume between synthetic and real PET were calculated. Two additional open-source glioma databases of preoperative CE MRI without methionine PET were used as the external test set. Using the TBRs, the area under the receiver operating characteristic curve (AUC) for classifying high-grade and low-grade gliomas and overall survival were evaluated. Results The institutional data set included 362 patients (mean age, 49 years ± 19 [SD]; 195 female, 167 male; training, n = 294; validation, n = 34; test, n = 34). In the internal test set, Pearson correlation coefficients were 0.68 (95% CI: 0.47, 0.81), 0.76 (95% CI: 0.59, 0.86), and 0.92 (95% CI: 0.85, 0.95) for TBRmax, TBRmean, and lesion volume, respectively. The external test set included 344 patients with gliomas (mean age, 53 years ± 15; 192 male, 152 female; high grade, n = 269). The AUC for TBRmax was 0.81 (95% CI: 0.75, 0.86) and the overall survival analysis showed a significant difference between the high (2-year survival rate, 27%) and low (2-year survival rate, 71%; P < .001) TBRmax groups. Conclusion The AI-based model-generated synthetic methionine PET images strongly correlated with real PET images and showed good performance for glioma grading and prognostication. Published under a CC BY 4.0 license. Supplemental material is available for this article.

    DOI: 10.1148/radiol.223016

    PubMed

  • The Association of Metabolic Brain <scp>MRI</scp>, Amyloid <scp>PET</scp>, and Clinical Factors: A Study of Alzheimer's Disease and Normal Controls From the Open Access Series of Imaging Studies Dataset Reviewed

    Shu Matsushita, Hiroyuki Tatekawa, Daiju Ueda, Hirotaka Takita, Daisuke Horiuchi, Taro Tsukamoto, Taro Shimono, Yukio Miki

    Journal of Magnetic Resonance Imaging   2023.07( ISSN:1053-1807 ( eISSN:1522-2586

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    Publishing type:Research paper (scientific journal)  

    DOI: 10.1002/jmri.28892

    PubMed

  • ChatGPT's Diagnostic Performance from Patient History and Imaging Findings on the Diagnosis Please Quizzes. Reviewed

    Daiju Ueda, Yasuhito Mitsuyama, Hirotaka Takita, Daisuke Horiuchi, Shannon L Walston, Hiroyuki Tatekawa, Yukio Miki

    Radiology   308 ( 1 )   e231040   2023.07( ISSN:00338419

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    Publishing type:Research paper (scientific journal)   International / domestic magazine:International journal  

    DOI: 10.1148/radiol.231040

    PubMed

  • Improved reproducibility of diffusion tensor image analysis along the perivascular space(DTI-ALPS) index: an analysis of reorientation technique of the OASIS-3 dataset(タイトル和訳中)

    Tatekawa Hiroyuki, Matsushita Shu, Ueda Daiju, Takita Hirotaka, Horiuchi Daisuke, Atsukawa Natsuko, Morishita Yuka, Tsukamoto Taro, Shimono Taro, Miki Yukio

    Japanese Journal of Radiology   41 ( 4 )   393 - 400   2023.04( ISSN:1867-1071

  • Brain temperature remains stable during the day: a study of diffusion-weighted imaging thermometry in healthy individuals. Reviewed

    Daisuke Horiuchi, Taro Shimono, Hiroyuki Tatekawa, Taro Tsukamoto, Hirotaka Takita, Shu Matsushita, Yukio Miki

    Neuroradiology   65 ( 8 )   1239 - 1246   2023.03( ISSN:00283940

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    Publishing type:Research paper (scientific journal)   International / domestic magazine:International journal  

    PURPOSE: To investigate the daily fluctuations in brain temperature in healthy individuals using magnetic resonance (MR) diffusion-weighted imaging (DWI) thermometry and to clarify the associations between the brain and body temperatures and sex. METHODS: Thirty-two age-matched healthy male and female volunteers (male = 16, 20-38 years) were recruited between July 2021 and January 2022. Brain MR examinations were performed in the morning and evening phases on the same day to calculate the brain temperatures using DWI thermometry. Body temperature was also measured in each MR examination. Group comparisons of body and brain temperatures between the two phases were performed using paired t-tests. A multiple linear regression model was used to predict the morning brain temperature using sex, evening brain temperature, and the interaction between sex and evening brain temperature as covariates. RESULTS: Body temperatures were significantly higher in the evening than in the morning in all participants, male group, and female group (p < 0.001, = 0001, and < 0.001, respectively). Meanwhile, no significant difference was observed between the morning and evening brain temperatures in each analysis (p = 0.23, 0.70, and 0.16, respectively). Multiple linear regression analysis showed significant associations of morning brain temperature with sex (p = 0.038), evening brain temperature (p < 0.001), and the interaction between sex and evening brain temperature (p = 0.036). CONCLUSION: Unlike body temperature, brain temperature showed no significant daily fluctuations; however, daily fluctuations in brain temperature may vary depending on sex.

    DOI: 10.1007/s00234-023-03142-9

    PubMed

  • Correlation between Phase-difference-enhanced MR Imaging and Amyloid Positron Emission Tomography: A Study on Alzheimer's Disease Patients and Normal Controls(タイトル和訳中)

    Takita Hirotaka, Doishita Satoshi, Yoneda Tetsuya, Takekawa Hiroyuki, Abe Takato, Itoh Yoshiaki, Horiuchi Daisuke, Tsukamoto Taro, Shimono Taro, Miki Yukio

    Magnetic Resonance in Medical Sciences   22 ( 1 )   67 - 78   2023.01( ISSN:1347-3182

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    Alzheimer病(AD)の大脳皮質中アミロイド-β沈着はアミロイドPETにより評価されるが、アミロイド-β関連鉄は位相差強調画像化法(PADRE)で検出される。本報ではPADREイメージングの低強度領域と、11C-Pittzburg compound Bを用いたアミロイドPET(11C-PiB PET)集積との相関性について検討した。2015年1月~2018年4月にかけ、11C-PiB PET検査を受けたAD患者8例(後向きに3例、前向きに5例)と年齢をマッチさせた健常対照者10例を対象に、楔部、楔前部、上前頭回(SFG)、上側頭回(STG)のROIを自動セグメント化した。視覚的評価による4点スケール法や体積の半定量評価(低強度領域の体積百分率)から、各ROIのPADREイメージングにおける低強度領域を評価し、アミロイドPETでは各ROIの平均SUV比(SUVR)を算出した。PADREイメージングにおける4点スケール法とアミロイドPETのSUVR間、体積の半定量評価とSUVR間におけるSpearman相関係数を評価した結果、楔前部では全例にPADREイメージングによる4点スケール法とアミロイドPETのSUVR間で有意な正相関が同定された。また、楔部では、全例にPADREイメージングの半定量評価による体積の百分率とアミロイドPETのSUVR間で、有意な正相関が認められた。以上より、アミロイド-β増強PADREイメージングは、特に楔部や楔前部ではアミロイドPETのSUVR予測に有用と考えられたことから、アミロイド沈着検出によるAD診断への適用が期待された。

  • Application of AI-driven Image to Image Translation Techniques in Neuroradiology Invited

    Takita Hirotaka, Ueda Daiju

    Medical Imaging and Information Sciences   40 ( 4 )   66 - 74   2023( ISSN:09101543 ( eISSN:18804977

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    Publishing type:Research paper (scientific journal)  

    <p>In recent years, the rapid evolution of artificial intelligence (AI) has brought about a revolution in medical research. In particular, the application of AI technology to medical imaging is expanding rapidly, with image-to-image translation technique gaining significant attention. Image-to-image translation technique allows for a wide range of applications, such as converting between different imaging modalities and removing artifacts. It is expected to open up new perspectives that go beyond the traditional framework of medical imaging. Using image-to-image translation models, it’s possible to generate synthetic PET from MRI images, or convert images with artifacts to those without, potentially contributing to improved diagnostic accuracy and optimization of treatment plans. In this article, we introduce two papers we published applying image-to-image translation technique in the field of neuroradiology: a study on generating synthetic methionine PET using MRI, and a study on producing Digital Subtraction Angiography (DSA) without misregistration artifacts.</p>

    DOI: 10.11318/mii.40.66

  • Improved reproducibility of diffusion tensor image analysis along the perivascular space (DTI-ALPS) index: an analysis of reorientation technique of the OASIS-3 dataset Reviewed

    Hiroyuki Tatekawa, Shu Matsushita, Daiju Ueda, Hirotaka Takita, Daisuke Horiuchi, Natsuko Atsukawa, Yuka Morishita, Taro Tsukamoto, Taro Shimono, Yukio Miki

    Japanese Journal of Radiology   41 ( 4 )   393 - 400   2022.12( ISSN:1867-1071 ( eISSN:1867-108X

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    Publishing type:Research paper (scientific journal)  

    Abstract

    Purpose

    Diffusion tensor image analysis along the perivascular space (DTI-ALPS) index is intended to reflect the glymphatic function of the brain; however, head rotation may reduce reproducibility and reliability. This study aimed to evaluate whether reorientation of DTI data improves the reproducibility of the ALPS index using the OASIS-3 dataset.

    Materials and methods

    234 cognitively normal subjects from the OASIS-3 dataset were included. Original and reoriented ALPS indices were calculated using a technique that registered vector information of DTI to another space and created reoriented diffusivity maps. The F test was used to compare variances of the original and reoriented ALPS indices. Subsequently, subjects with head rotation around the z- (inferior-superior; n = 43) or x axis (right-left; n = 25) and matched subjects with neutral head position were selected for evaluation of intra- and inter-rater reliability. Intraclass correlation coefficients (ICCs) of the original and reoriented ALPS indices for participants with head rotation and neutral head position were calculated separately. The Bland–Altman plot comparing the original and reoriented ALPS indices was also evaluated.

    Results

    The reoriented ALPS index exhibited a significantly smaller variance than the original ALPS index (p &lt; 0.001). For intra- and inter-reliability, the reorientation technique showed good-to-excellent reproducibility in calculating the ALPS index even in subjects with head rotation (ICCs of original ALPS index: 0.52–0.81; ICCs of reoriented ALPS index: &gt; 0.85). A wider range of the 95% limit of agreement of the Bland–Altman plot for subjects with x axis rotation was identified, indicating that x axis rotation may remarkably affect calculation of the ALPS index.

    Conclusion

    The technique used in this study enabled the creation of reoriented diffusivity maps and improved reproducibility in calculating the ALPS index.

    DOI: 10.1007/s11604-022-01370-2

    PubMed

    Other URL: https://link.springer.com/article/10.1007/s11604-022-01370-2/fulltext.html

  • Frequency and imaging features of the adjacent osseous changes of salivary gland carcinomas in the head and neck region. Reviewed

    Daisuke Horiuchi, Taro Shimono, Hiroyuki Tatekawa, Taro Tsukamoto, Hirotaka Takita, Masahiro Okazaki, Yukio Miki

    Neuroradiology   64 ( 9 )   1869 - 1877   2022.09( ISSN:00283940

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    Publishing type:Research paper (scientific journal)   International / domestic magazine:International journal  

    PURPOSE: The association between salivary gland carcinomas and adjacent osseous changes in the head and neck region is not clear. We evaluated the frequency and imaging features of such changes and investigated the specific characteristics of salivary gland carcinomas associated with them. METHODS: A total of 118 patients with histologically proven salivary gland carcinomas were retrospectively reviewed. The imaging characteristics of osseous changes were sorted into three categories based on computed tomography images: sclerotic change, erosive change, and lytic change. The frequency of all these osseous changes and any one of them was compared between different pathologies using Fisher's exact test. Odds ratios were calculated to evaluate the association between these changes and perineural spread. RESULTS: Osseous changes were found in 21 (18%) of 118 cases. Among these, seven (6%) cases were with sclerotic, nine (8%) with erosive, and nine (8%) with lytic changes (four with mixed change). Adenoid cystic carcinoma showed a significantly higher frequency of sclerotic and erosive changes, and either osseous change, than the other salivary gland carcinomas (p < 0.001 for each). Sclerotic changes were only present in the adenoid cystic carcinomas. Perineural spread was a significant factor in showing higher osseous change frequencies (odds ratio = 3.98, p = 0.006). CONCLUSION: Among salivary gland carcinomas in the head and neck region, adenoid cystic carcinomas had a significantly higher frequency of adjacent osseous changes, especially sclerotic changes, than other salivary gland carcinomas.

    DOI: 10.1007/s00234-022-02972-3

    PubMed

  • Orbital apex schwannoma with a high titer of proteinase 3 antineutrophil cytoplasmic antibody. Reviewed

    Tatsushi Oura, Taro Shimono, Maciej Pas, Hirotaka Takita, Daisuke Horiuchi, Yasuhito Mitsuyama, Yukio Miki

    Radiology case reports   17 ( 4 )   1120 - 1123   2022.04

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    International / domestic magazine:International journal  

    Here, we present a very unusual case of orbital apex schwannoma with a high titer of proteinase 3 antineutrophil cytoplasmic antibody (PR3-ANCA). A 67-year-old man presented with a 3-month history of double vision. Radiological examinations revealed a mass lesion at the left orbital apex, and laboratory examination revealed a high titer of PR3-ANCA, of 49.1 U/mL (reference range<2.0). After the surgery, the lesion was histologically diagnosed as schwannoma, and the PR3-ANCA titer decreased to 8.4 U/m. Although making a correct diagnosis of orbital apex schwannoma may be difficult due to the need to differentiate from granulomatosis with polyangiitis when PR3-ANCA serum levels are elevated, careful examination of the radiological findings may aid the diagnosis.

    DOI: 10.1016/j.radcr.2022.01.047

    PubMed

  • Malignant transformation of a dysembryoplastic neuroepithelial tumor presenting with intraventricular hemorrhage. Reviewed

    Hirotaka Takita, Taro Shimono, Takehiro Uda, Hayato Ikota, Toshiyuki Kawashima, Daisuke Horiuchi, Eisaku Terayama, Taro Tsukamoto, Yukio Miki

    Radiology case reports   17 ( 3 )   939 - 943   2022.03

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    Authorship:Lead author   International / domestic magazine:International journal  

    Dysembryoplastic neuroepithelial tumors (DNTs) are benign brain tumors classified as grade 1 in the 2021 World Health Organization (WHO) classification of central nervous system tumors. DNTs rarely undergo malignant transformation and cause symptomatic intracranial hemorrhage. We report a case of malignant transformation of DNT presenting with intraventricular hemorrhage and review the literature on malignant transformation of DNTs. An 18-year-old woman with a history of epilepsy presented with a sudden headache and vomiting. Radiological examination revealed a mass lesion in the left parietal lobe and intraventricular hemorrhage. The patient underwent an emergency craniotomy for brain tumor resection. The lesion was pathologically diagnosed as a malignant transformation of DNT. She had been followed up without tumor recurrence for 2 years after surgery.

    DOI: 10.1016/j.radcr.2022.01.014

    PubMed

  • Correlation between Phase-Difference-Enhanced MR Imaging and Amyloid Positron Emission Tomography: A Study on Alzheimer's Disease Patients and Normal Controls. Reviewed

    Hirotaka Takita, Satoshi Doishita, Tetsuya Yoneda, Hiroyuki Tatekawa, Takato Abe, Yoshiaki Itoh, Daisuke Horiuchi, Taro Tsukamoto, Taro Shimono, Yukio Miki

    Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine   22 ( 1 )   67 - 78   2022.01

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    Authorship:Lead author   Publishing type:Research paper (scientific journal)   International / domestic magazine:Domestic journal  

    PURPOSE: While amyloid-β deposition in the cerebral cortex for Alzheimer's disease (AD) is often evaluated by amyloid positron emission tomography (PET), amyloid-β-related iron can be detected using phase difference enhanced (PADRE) imaging; however, no study has validated the association between PADRE imaging and amyloid PET. This study investigated whether the degree of hypointense areas on PADRE imaging correlated with the uptake of amyloid PET. METHODS: PADRE imaging and amyloid PET were performed in 8 patients with AD and 10 age-matched normal controls. ROIs in the cuneus, precuneus, superior frontal gyrus (SFG), and superior temporal gyrus (STG) were automatically segmented. The degree of hypointense areas on PADRE imaging in each ROI was evaluated using 4-point scaling of visual assessment or volumetric semiquantitative assessment (the percentage of hypointense volume within each ROI). The mean standardized uptake value ratio (SUVR) of amyloid PET in each ROI was also calculated. The Spearman's correlation coefficient between the 4-point scale of PADRE imaging and SUVR of amyloid PET or between the semiquantitative hypointense volume percentage and SUVR in each ROI was evaluated. RESULTS: In the precuneus, a significant positive correlation was identified between the 4-point scale of PADRE imaging and SUVR of amyloid PET (Rs = 0.5; P = 0.034) in all subjects. In the cuneus, a significant positive correlation was identified between the semiquantitative volume percentage of PADRE imaging and SUVR of amyloid PET (Rs = 0.55; P = 0.02) in all subjects. CONCLUSION: Amyloid-β-enhancing PADRE imaging can be used to predict the SUVR of amyloid PET, especially in the cuneus and precuneus, and may have the potential to be used for diagnosing AD by detecting amyloid deposition.

    DOI: 10.2463/mrms.mp.2021-0123

    PubMed

  • Deep Learning-based Angiogram Generation Model for Cerebral Angiography without Misregistration Artifacts. Reviewed

    Daiju Ueda, Yutaka Katayama, Akira Yamamoto, Tsutomu Ichinose, Hironori Arima, Yusuke Watanabe, Shannon L Walston, Hiroyuki Tatekawa, Hirotaka Takita, Takashi Honjo, Akitoshi Shimazaki, Daijiro Kabata, Takao Ichida, Takeo Goto, Yukio Miki

    Radiology   299 ( 3 )   675 - 681   2021.06

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    Publishing type:Research paper (scientific journal)   International / domestic magazine:International journal  

    Background Digital subtraction angiography (DSA) generates an image by subtracting a mask image from a dynamic angiogram. However, patient movement-caused misregistration artifacts can result in unclear DSA images that interrupt procedures. Purpose To train and to validate a deep learning (DL)-based model to produce DSA-like cerebral angiograms directly from dynamic angiograms and then quantitatively and visually evaluate these angiograms for clinical usefulness. Materials and Methods A retrospective model development and validation study was conducted on dynamic and DSA image pairs consecutively collected from January 2019 through April 2019. Angiograms showing misregistration were first separated per patient by two radiologists and sorted into the misregistration test data set. Nonmisregistration angiograms were divided into development and external test data sets at a ratio of 8:1 per patient. The development data set was divided into training and validation data sets at ratio of 3:1 per patient. The DL model was created by using the training data set, tuned with the validation data set, and then evaluated quantitatively with the external test data set and visually with the misregistration test data set. Quantitative evaluations used the peak signal-to-noise ratio (PSNR) and the structural similarity (SSIM) with mixed liner models. Visual evaluation was conducted by using a numerical rating scale. Results The training, validation, nonmisregistration test, and misregistration test data sets included 10 751, 2784, 1346, and 711 paired images collected from 40 patients (mean age, 62 years ± 11 [standard deviation]; 33 women). In the quantitative evaluation, DL-generated angiograms showed a mean PSNR value of 40.2 dB ± 4.05 and a mean SSIM value of 0.97 ± 0.02, indicating high coincidence with the paired DSA images. In the visual evaluation, the median ratings of the DL-generated angiograms were similar to or better than those of the original DSA images for all 24 sequences. Conclusion The deep learning-based model provided clinically useful cerebral angiograms free from clinically significant artifacts directly from dynamic angiograms. Published under a CC BY 4.0 license. Supplemental material is available for this article.

    DOI: 10.1148/radiol.2021203692

    PubMed

  • 脳室内出血をきたした側脳室内髄膜腫の1例

    竹内 均, 下野 太郎, 田北 大昂, 宇田 武弘, 中条 公輔, 大浦 達史, 田中 里可子, 三木 幸雄

    臨床放射線   66 ( 2 )   157 - 160   2021.02( ISSN:0009-9252

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    症例は50歳代女性で、突然の右側頭部痛があり、その後嘔吐を繰り返した。救急搬送時の単純CTで右側脳室三角部を中心とした4×3×3cm大の腫瘤性病変を認めた。腫瘤の形態は円形で境界明瞭であり、内部は均一かつ灰白質と等吸収で、石灰化は認めなかった。右側脳室内には出血を伴っていた。第6病日のMRIで右側脳室内腫瘤は、T1強調像で白質より軽度低信号、T2強調像で白質より高信号で、拡散強調像では高信号、ADC mapでは拡散は白質と同程度であった。磁化率強調像では腫瘤辺縁に点状または線状の低信号を認め、出血と考えられた。腫瘤は均一な造影効果を示し、右側脳室三角部周囲の白質に浮腫を認めた。画像所見から、髄膜腫、脳室内(脈絡叢)転移、solitary fibrous tumor/hemangiopericytomaが疑われた。手術では、栄養血管である前脈絡叢動脈を脳室内で凝固切断した。脳室壁と腫瘤を分けつつ、三角部の脈絡叢は腫瘤とともに摘出した。摘出検体の病理組織所見では、紡錘形の細胞が渦巻き状に増生している所見や、紡錘形の細胞が索状に配列している所見、楕円形の細胞が増生している所見を認めた。以上から、移行性髄膜腫grade Iと診断された。

  • DWI scoring system for prognosis of acute encephalopathy with biphasic seizures and late reduced diffusion. Reviewed

    Hirotaka Takita, Taro Shimono, Takao Manabe, Ichiro Kuki, Kiyoko Amo, Masao Togawa, Yukio Miki

    Japanese journal of radiology   38 ( 9 )   860 - 869   2020.09

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    Authorship:Lead author   Publishing type:Research paper (scientific journal)   International / domestic magazine:Domestic journal  

    PURPOSE: The aim of this study was to predict neurological outcomes for acute encephalopathy with biphasic seizures and late reduced diffusion (AESD) using diffusion-weighted imaging (DWI), and assess relationships between anatomical sites of lesions and their outcomes. MATERIALS AND METHODS: We assessed DWI abnormalities and neurological outcomes in 30 patients with AESD, and classified patients into severe and non-severe groups according to their neurological outcomes. We also established a DWI scoring system as follows: zero for normal, and one for lesion at each location. Differences between the severe and non-severe groups were examined, and receiver operating characteristic (ROC) curve analysis was performed. RESULTS: Nine (30%) patients were classified into the severe group. On DWI, patients in the severe group were more likely to have temporal lobe (P = 0.014), perirolandic (P = 0.008), and corpus callosum (P = 0.0008) lesions than those in the non-severe group. The total DWI scores were significantly higher in the severe group than those in the non-severe group (P = 0.0002). ROC curve showed an area under the curve of 0.929, with a cutoff value of five, sensitivity of 88.9%, and specificity of 81.0%. CONCLUSION: Patients with severe AESD had more extensive DWI abnormalities than those with non-severe AESD. Our DWI scoring system may be useful for the prediction of outcomes of AESD. Widespread lesions seemed to have stronger influence on outcomes than each lesion location.

    DOI: 10.1007/s11604-020-00984-8

    PubMed

  • 痙攣重積型二相性急性脳症の予後予測に対するDWIスコアリングシステム(DWI scoring system for prognosis of acute encephalopathy with biphasic seizures and late reduced diffusion)

    Takita Hirotaka, Shimono Taro, Manabe Takao, Kuki Ichiro, Amo Kiyoko, Togawa Masao, Miki Yukio

    Japanese Journal of Radiology   38 ( 9 )   860 - 869   2020.09( ISSN:1867-1071

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    拡散強調画像(DWI)の定量解析を行い、痙攣重積型二相性急性脳症(AESD)患者に描出された拡散制限域をスコア化することにより、神経学的転帰を予測し、病変の解剖学的部位と転帰との関連性を評価した。AESD患者30例を対象として、DWI異常と神経学的転帰の評価を行い、神経学的転帰は重症度により、重症群(9例)および非重症群(21例)に分類した。また、正常の場合は0、各部位における病変を1とする DWIスコアリングシステムを適用し、重症群と非重症群を比較した。その結果、重症群では非重症群に比べ、DWI上に側頭葉、ローランド裂周囲および脳梁に病変が多く認められ、DWI総スコアにおいても、重症群では非重症群に比べ有意に高値であった。さらに、ROC解析により、重症群および非重症群のDWI総スコアによる判別を行ったところ、AUCは0.929カットオフ値5における感度と特異度が、各々88.9%と81.0%であることが確認された。以上より、重症AESD患者は非重症AESD患者に比べ、DWI異常が広範囲に及び、DWIスコアリングシステムはAESD転帰予測に有用であることが示され、病変部位ではなく、病変範囲が転帰に強い影響を及ぼすことが示唆された。

  • 巨大脳動脈瘤と椎骨動脈解離を合併したTurner症候群の1例

    原田 翔平, 下野 太郎, 田北 大昂, 三木 幸雄

    臨床放射線   65 ( 3 )   277 - 281   2020.03( ISSN:0009-9252

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    20歳代女性。頭痛・嘔気・複視を主訴に受診した、幼少期にTurner症候群と診断されていた。頭部MRIとCT angiographyで左後大脳動脈に嚢状動脈瘤を認めたほか、左椎骨動脈に口径不整を認め、左椎骨動脈解離と診断した。健常な右椎骨動脈を経由してコイル塞栓術を施行したところ、カテーテル操作により右椎骨動脈解離が生じ、原因として脳血管の脆弱性が考えられた。3ヵ月後、右椎骨動脈解離が改善したことを確認のうえ左後大脳動脈のコイル塞栓術を行い、術後3年の現在まで動脈瘤の増大は認めていない。

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Books and Other Publications

  • 300例で学ぶ読影レポートの流儀 : MRI,CT,X線,PETまで完全理解

    田北大昂( Role: Contributor)

    Gakken  2023.01  ( ISBN:9784780904437

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    Total pages:383p  

    CiNii Books

  • 頭部画像診断の勘ドコロNEO

    田北大昂( Role: Contributor)

    メジカルビュー社  2021.02  ( ISBN:9784758316132

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    Total pages:xvi, 535p  

    CiNii Books

MISC

  • 【診断・治療のための意思決定AI】人工知能による画像変換技術の神経放射線領域への応用について

    田北 大昂, 植田 大樹

    医用画像情報学会雑誌   40 ( 4 )   66 - 74   2023.12( ISSN:0910-1543

  • Response: Evaluating Diagnostic Performance of ChatGPT in Radiology: Delving into Methods

    Ueda D.

    Radiology   308 ( 3 )   1 - 2   2023( ISSN:00338419

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  • 頭頸部領域の唾液腺癌における隣接する骨の変化の頻度や画像的特徴

    堀内 大右, 下野 太郎, 立川 裕之, 塚本 太朗, 田北 大昂, 岡崎 真大, 松下 周, 三木 幸雄

    日本医学放射線学会秋季臨床大会抄録集   58回   S403 - S403   2022.08( ISSN:0048-0428 ( eISSN:1347-7951

  • COVID-19関連肺アスペルギルス症(COVID-19-associated pulmonary aspergillosis:CAPA)の2例

    堀内 大右, 下野 太郎, 田北 大昴, 山本 啓雅, 中嶋 康博, 中舎 洋輔, 井本 和紀, 山田 康一, 掛屋 弘, 三木 幸雄

    日本医学放射線学会秋季臨床大会抄録集   57回   S395 - S395   2021.08( ISSN:0048-0428 ( eISSN:1347-7951

  • 脳室内出血をきたした側脳室内髄膜腫の1例

    竹内 均, 下野 太郎, 田北 大昂, 宇田 武弘, 中条 公輔, 大浦 達史, 田中 里可子, 三木 幸雄

    臨床放射線   66 ( 2 )   157 - 160   2021.02( ISSN:0009-9252

     More details

    症例は50歳代女性で、突然の右側頭部痛があり、その後嘔吐を繰り返した。救急搬送時の単純CTで右側脳室三角部を中心とした4×3×3cm大の腫瘤性病変を認めた。腫瘤の形態は円形で境界明瞭であり、内部は均一かつ灰白質と等吸収で、石灰化は認めなかった。右側脳室内には出血を伴っていた。第6病日のMRIで右側脳室内腫瘤は、T1強調像で白質より軽度低信号、T2強調像で白質より高信号で、拡散強調像では高信号、ADC mapでは拡散は白質と同程度であった。磁化率強調像では腫瘤辺縁に点状または線状の低信号を認め、出血と考えられた。腫瘤は均一な造影効果を示し、右側脳室三角部周囲の白質に浮腫を認めた。画像所見から、髄膜腫、脳室内(脈絡叢)転移、solitary fibrous tumor/hemangiopericytomaが疑われた。手術では、栄養血管である前脈絡叢動脈を脳室内で凝固切断した。脳室壁と腫瘤を分けつつ、三角部の脈絡叢は腫瘤とともに摘出した。摘出検体の病理組織所見では、紡錘形の細胞が渦巻き状に増生している所見や、紡錘形の細胞が索状に配列している所見、楕円形の細胞が増生している所見を認めた。以上から、移行性髄膜腫grade Iと診断された。

    Other URL: https://search.jamas.or.jp/default/link?pub_year=2021&ichushi_jid=J01565&link_issn=&doc_id=20210219150007&doc_link_id=10.18888%2Frp.0000001517&url=https%3A%2F%2Fdoi.org%2F10.18888%2Frp.0000001517&type=%E5%8C%BB%E6%9B%B8.jp_%E3%82%AA%E3%83%BC%E3%83%AB%E3%82%A2%E3%82%AF%E3%82%BB%E3%82%B9&icon=https%3A%2F%2Fjk04.jamas.or.jp%2Ficon%2F00024_2.gif

  • 巨大脳動脈瘤と椎骨動脈解離を合併したTurner症候群の1例

    原田 翔平, 下野 太郎, 田北 大昂, 三木 幸雄

    臨床放射線   65 ( 3 )   277 - 281   2020.03( ISSN:0009-9252

     More details

    20歳代女性。頭痛・嘔気・複視を主訴に受診した、幼少期にTurner症候群と診断されていた。頭部MRIとCT angiographyで左後大脳動脈に嚢状動脈瘤を認めたほか、左椎骨動脈に口径不整を認め、左椎骨動脈解離と診断した。健常な右椎骨動脈を経由してコイル塞栓術を施行したところ、カテーテル操作により右椎骨動脈解離が生じ、原因として脳血管の脆弱性が考えられた。3ヵ月後、右椎骨動脈解離が改善したことを確認のうえ左後大脳動脈のコイル塞栓術を行い、術後3年の現在まで動脈瘤の増大は認めていない。

    Other URL: https://search.jamas.or.jp/default/link?pub_year=2020&ichushi_jid=J01565&link_issn=&doc_id=20200403110013&doc_link_id=10.18888%2Frp.0000001173&url=https%3A%2F%2Fdoi.org%2F10.18888%2Frp.0000001173&type=%E5%8C%BB%E6%9B%B8.jp_%E3%82%AA%E3%83%BC%E3%83%AB%E3%82%A2%E3%82%AF%E3%82%BB%E3%82%B9&icon=https%3A%2F%2Fjk04.jamas.or.jp%2Ficon%2F00024_2.gif

  • Dual energy CTにより頭蓋内出血とヨード造影剤漏出の鑑別を試みた3例

    田北 大昂, 甲田 洋一, 小川 博之, 阪中 英里加, 井上 奈穂子, 崔 朝理, 大隈 志保, 市來 真, 村田 佳津子, 真鍋 隆夫

    Japanese Journal of Radiology   38 ( Suppl. )   40 - 40   2020.02( ISSN:1867-1071 ( eISSN:1867-108X

  • 成人発症したmegalencephalic leukoencephalopathy with subcortical cystsの1例

    阪中 英里加, 田北 大昂, 小川 博之, 井上 奈穂子, 崔 朝理, 大隈 志保, 市來 真, 甲田 洋一, 村田 佳津子, 真鍋 隆夫, 井上 佑一

    Japanese Journal of Radiology   38 ( Suppl. )   35 - 35   2020.02( ISSN:1867-1071 ( eISSN:1867-108X

  • HIV陰性患者に発症した進行性多巣性白質脳症の1例

    田北 大昂, 小川 博之, 阪中 英里加, 井上 奈穗子, 崔 朝理, 大隈 志保, 市來 真, 甲田 洋一, 村田 佳津子, 真鍋 隆夫, 井上 佑一, 福島 裕子

    Japanese Journal of Radiology   38 ( Suppl. )   35 - 35   2020.02( ISSN:1867-1071 ( eISSN:1867-108X

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Presentations

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Grant-in-Aid for Scientific Research

  • 人工知能によるMRI画像からの疑似PET画像への変換アルゴリズムの作成

    Grant-in-Aid for Early-Career Scientists  2027

  • 人工知能によるMRI画像からの疑似PET画像への変換アルゴリズムの作成

    Grant-in-Aid for Early-Career Scientists  2026

  • 人工知能によるMRI画像からの疑似PET画像への変換アルゴリズムの作成

    Grant-in-Aid for Early-Career Scientists  2025

  • 人工知能によるMRI画像からの疑似PET画像への変換アルゴリズムの作成

    Grant-in-Aid for Early-Career Scientists  2024