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Raul-Ronald Galea, Laura Diosan, Anca Andreica, Loredana Popa, Simona Manole and Zoltán Bálint
Despite the promising results obtained by deep learning methods in the field of medical image segmentation, lack of sufficient data always hinders performance to a certain degree. In this work, we explore the feasibility of applying deep learning methods...
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Gonzalo E. Mosquera-Rojas, Cylia Ouadah, Azadeh Hadadi, Alain Lalande and Sarah Leclerc
The extent of myocardial infarction (MI) can be evaluated thanks to delayed enhancement (DE) cardiac MRI. DE MRI is an imaging technique acquired several minutes after the injection of a contrast agent where MI appears with a bright signal. The automatic...
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Fumin Guo, Matthew Ng, Idan Roifman and Graham Wright
Cardiac MRI is the gold standard for evaluating left ventricular myocardial mass (LVMM), end-systolic volume (LVESV), end-diastolic volume (LVEDV), stroke volume (LVSV), and ejection fraction (LVEF). Deep convolutional neural networks (CNNs) can provide ...
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Youssef Skandarani, Pierre-Marc Jodoin and Alain Lalande
Deep learning methods are the de facto solutions to a multitude of medical image analysis tasks. Cardiac MRI segmentation is one such application, which, like many others, requires a large number of annotated data so that a trained network can generalize...
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Alejandra Ortega, João Pedrosa, Brecht Heyde, Ling Tong and Jan D?hooge
Fast volumetric cardiac imaging requires reducing the number of transmit events within a single volume. One way of achieving this is by limiting the field of view (FOV) of the recording to the myocardium when investigating cardiac mechanics. Although ful...
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Riyanto Sigit, Zainal Arief, Mochamad Mobed Bachtiar
Pág. 99 - 114
The main problem encountered nowadays in the health field, especially in health care is the growing number of population and the decreasing health facilities. In this regard, healthcare kiosk is used as an alternative to the health care facilities. Heart...
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