Medical Image Reconstruction

Gengsheng Lawrence Zeng

ISBN 10: 3111055035 / ISBN 13: 9783111055039

Verlag: Walter De Gruyter Jul 2023, 2023

Beschreibung

Neuware -This textbook introduces the essential concepts of tomography in the field of medical imaging. The medical imaging modalities include x-ray CT (computed tomography), PET (positron emission tomography), SPECT (single photon emission tomography) and MRI. In these modalities, the measurements are not in the image domain and the conversion from the measurements to the images is referred to as the image reconstruction. The work covers various image reconstruction methods, ranging from the classic analytical inversion methods to the optimization-based iterative image reconstruction methods. As machine learning methods have lately exhibited astonishing potentials in various areas including medical imaging the author devotes one chapter to applications of machine learning in image reconstruction. Based on college level in mathematics, physics, and engineering the textbook supports students in understanding the concepts. It is an essential reference for graduate students and engineers with electrical engineering and biomedical background due to its didactical structure and the balanced combination of methodologies and applications, 273 pp. Englisch.

Bestandsnummer des Verkäufers 9783111055039

Bibliografische Details

• Titel: Medical Image Reconstruction
• Verlag: Walter De Gruyter Jul 2023
• Erscheinungsjahr: 2023
• Sprache: Englisch
• ISBN-10: 3111055035
• ISBN-13: 9783111055039
• Einband: Taschenbuch
• Auflage: 2. Auflage
• Zustand: Neu
• Abmessungen: 240B x 170 H x 17 T Millimeter Breite: 240 mm, Höhe: 170 mm, Tiefe: 17 mm
• Gewicht: 490 Gramm

Über diesen Titel

Inhaltsangabe

This textbook introduces the essential concepts of tomography in the field of medical imaging. The medical imaging modalities include x-ray CT (computed tomography), PET (positron emission tomography), SPECT (single photon emission tomography) and MRI. In these modalities, the measurements are not in the image domain and the conversion from the measurements to the images is referred to as the image reconstruction. The work covers various image reconstruction methods, ranging from the classic analytical inversion methods to the optimization-based iterative image reconstruction methods. As machine learning methods have lately exhibited astonishing potentials in various areas including medical imaging the author devotes one chapter to applications of machine learning in image reconstruction. Based on college level in mathematics, physics, and engineering the textbook supports students in understanding the concepts. It is an essential reference for graduate students and engineers with electrical engineering and biomedical background due to its didactical structure and the balanced combination of methodologies and applications,

Über die Autorin bzw. den Autor

Gengsheng Lawrence Zeng, Weber State University, Odgen, USA.