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Dive into the research topics where Artificial Intelligence in Medical Imaging Development is active. These topic labels come from the works of this organisation's members. Together they form a unique fingerprint.
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Measurement of effective renal plasma flow using model analysis of dynamic CT in the preoperative evaluation of the renal transplant donors
Kataoka, Y., Nishio, H., Matsukiyo, R., Kato, R., Hasegawa, M., Kenmochi, T., Shiroki, R., Toyama, H., Ichihara, T. & Kobayashi, S., 2020, In: Fujita Medical Journal. 6, 3, p. 73-80 8 p.Research output: Contribution to journal › Article › peer-review
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Development of calibration phantoms for generating quantitative perfusion images using 2D angiography data
Sakaguchi, T., Natsume, T., Kanamori, Y. & Ichihara, T., 10-03-2016, 2014 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2014. Institute of Electrical and Electronics Engineers Inc., 7430847. (2014 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2014).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
1 Link opens in a new tab Citation (Scopus) -
Underestimation of myocardial blood flow by dynamic perfusion CT: Explanations by two-compartment model analysis and limited temporal sampling of dynamic CT
Ishida, M., Kitagawa, K., Ichihara, T., Natsume, T., Nakayama, R., Nagasawa, N., Kubooka, M., Ito, T., Uno, M., Goto, Y., Nagata, M. & Sakuma, H., 01-06-2016, In: Journal of Cardiovascular Computed Tomography. 10, 3, p. 207-214 8 p.Research output: Contribution to journal › Article › peer-review
47 Link opens in a new tab Citations (Scopus)