Validation of quantitative perfusion cardiovascular magnetic resonance employing deconvolution techniques with Tofts, modified-Tofts, and Fermi function models against 15O-water positron emission tomography

ABSTRACT: Background: Quantitative perfusion cardiovascular magnetic resonance (QP-CMR) allows the generation of pixel-wise myocardial blood flow (MBF) maps using model-based deconvolution with several models including Tofts, modified-Tofts, and Fermi function models. However, the accuracy of pixel...

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Bibliographic Details

Main Authors:	Masafumi Takafuji, Masaki Ishida, Yasutaka Ichikawa, Satoshi Nakamura, Haruno Ito, Takanori Kokawa, Suguru Araki, Shintaro Yamaguchi, Naoki Hashimoto, Shiro Nakamori, Tairo Kurita, Kaoru Dohi, Hajime Sakuma
Format:	Artigo
Language:	Inglês
Published:	Elsevier 2026-01-01
Series:	Journal of Cardiovascular Magnetic Resonance
Subjects:	Coronary artery disease Coronary magnetic resonance angiography Deep learning Convolutional neural network Invasive coronary angiography
Online Access:	http://www.sciencedirect.com/science/article/pii/S1097664725008403
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