Medical Image Reconstruction : A Conceptual Tutorial

"Medical Image Reconstruction: A Conceptual Tutorial" introduces the classical and modern image reconstruction technologies, such as two-dimensional (2D) parallel-beam and fan-beam imaging, three-dimensional (3D) parallel ray, parallel plane, and cone-beam imaging. This book presents both...

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Auteur principal: Zeng, Gengsheng Lawrence
Format: Livre numérique
Langue:Anglais
Publié: Berlin, Heidelberg : Springer Berlin Heidelberg [20..].
Cham : Springer Nature
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Edition sous un autre format:• Medical Image Reconstruction, Texte imprimé, 9783642054518
• Medical Image Reconstruction, Texte imprimé, 9783642053672
Description
Résumé:"Medical Image Reconstruction: A Conceptual Tutorial" introduces the classical and modern image reconstruction technologies, such as two-dimensional (2D) parallel-beam and fan-beam imaging, three-dimensional (3D) parallel ray, parallel plane, and cone-beam imaging. This book presents both analytical and iterative methods of these technologies and their applications in X-ray CT (computed tomography), SPECT (single photon emission computed tomography), PET (positron emission tomography), and MRI (magnetic resonance imaging). Contemporary research results in exact region-of-interest (ROI) reconstruction with truncated projections, Katsevich's cone-beam filtered backprojection algorithm, and reconstruction with highly undersampled data with l0-minimization are also included. This book is written for engineers and researchers in the field of biomedical engineering specializing in medical imaging and image processing with image reconstruction. Gengsheng Lawrence Zeng is an expert in the development of medical image reconstruction algorithms and is a professor at the Department of Radiology, University of Utah, Salt Lake City, Utah, USA.
Description:Archives Springer e-books (Licence nationale)
Archives Springer e-books (Licence nationale)
ISBN:9783642053689
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Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. https://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017