Výsledky vyhledávání - "Muneeza Azmat"

Machine learned versus analytical models for estimation of Fractional Flow Reserve (FFR) from CT-derived information

Autor: Ethan Tu, Kelley R. Branch, Adam M. Alessio, Muneeza Azmat

Publikováno v: Medical Imaging 2021: Biomedical Applications in Molecular, Structural, and Functional Imaging.

Fractional Flow Reserve (FFR) is a widely used metric to quantify the functional significance of stenoses in coronary arteries. FFR is the ratio of pressure before and after a stenosis and is measured using a transducer during coronary catheterizatio

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::78586b689a10abd6c5f4be6bbbc5b3c0
https://doi.org/10.1117/12.2581701

Zobrazit plný text záznamu

Machine learned approach for estimating myocardial blood flow from dynamic CT and coronary artery disease risk factors

Autor: Ethan Tu, Kelley R. Branch, Muneeza Azmat, Adam M. Alessio

Publikováno v: Medical Imaging 2021: Biomedical Applications in Molecular, Structural, and Functional Imaging.

Estimating myocardial blood flow (MBF) is essential for diagnosing and risk stratifying myocardial ischemia. Currently, positron emission tomography (PET) is a gold standard for non-invasive, quantitative MBF measurements. In this work, we compare ou

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::875bb5e6bbe1d72852e4c78c685ce721
https://doi.org/10.1117/12.2581703

Zobrazit plný text záznamu

Vyhledávací nástroje:

Upřesnit hledání