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Applied Medical Image Processing
A Basic Course Anglais · Livre de poche

Expédition généralement dans un délai de 3 à 5 semaines

Description

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A widely used, classroom-tested text, Applied Medical Image Processing: A Basic Course delivers an ideal introduction to image processing in medicine, emphasizing the clinical relevance and special requirements of the field. Avoiding excessive mathematical formalisms, the book presents key principles by implementing algorithms from scratch and using simple MATLAB®/Octave scripts with image data and illustrations on an accompanying companion website. Organized as a complete textbook, it provides an overview of the physics of medical image processing and discusses imaging physics, clinical applications of image processing, image formats and data storage, intensity transforms, filtering of images and applications of the Fourier transform, three-dimensional spatial transforms, volume rendering, image registration, tomographic reconstruction and basic machine learning.
This Third Edition of the bestseller:


  • Contains a brand-new chapter on the basics of machine learning

  • Devotes more attention to the subject of color space

  • Includes additional examples from radiology, internal medicine, surgery, and radiation therapy

  • Incorporates freely available programs in the public domain (e.g., GIMP, 3DSlicer, and ImageJ) when applicable
Beneficial to students of medical physics, biomedical engineering, computer science, applied mathematics, and related fields, as well as medical physicists, radiographers, radiologists, and other professionals, Applied Medical Image Processing: A Basic Course, Third Edition is fully updated and expanded to ensure a perfect blend of theory and practice.
Wolfgang Birkfellner studied theoretical physics at, and holds a Ph.D in medical physics from, the University of Vienna, Austria. Currently, he is heading the Digital Image Processing Laboratory at the Center for Biomedical Engineering and Physics at the Medical University of Vienna. He is also a reviewer and editorial board member for major journals in the field, program committee member for international conferences, and principal investigator for several third-party funded research projects. Previously, he served as senior researcher at the University Hospital Basel/Switzerland and associate professor of medical physics at the Center for Biomedical Engineering and Physics of Vienna Medical School.


A propos de l'auteur










Wolfgang Birkfellner studied theoretical physics at, and holds a Ph.D in medical physics from, the University of Vienna, Austria. Currently, he is heading the Digital Image Processing Laboratory at the Center for Biomedical Engineering and Physics at the Medical University of Vienna. He is also a reviewer and editorial board member for major journals in the field, program committee member for international conferences, and principal investigator for several third-party funded research projects. Previously, he served as senior researcher at the University Hospital Basel/Switzerland and associate professor of medical physics at the Center for Biomedical Engineering and Physics of Vienna Medical School.


Détails du produit

Auteurs Birkfellner Wolfgang
Edition Taylor and Francis
 
Contenu Livre
Forme du produit Livre de poche
Date de parution 20.07.2026
Catégorie Sciences naturelles, médecine, it, technique > Médecine > Spécialités non cliniques
 
EAN 9781032122632
ISBN 978-1-032-12263-2
Nombre de pages 546
Illustrations schwarz-weiss Illustrationen, Raster,schwarz-weiss, Zeichnungen, schwarz-weiss, Tabellen, schwarz-weiss
Dimensions (emballage) 15,6 x 23,4 cm
Poids (emballage) 1 010 g
 
Catégories Medicine, Radiology, MEDICAL / Diagnostic Imaging / General, COMPUTERS / Image Processing, Electrical Engineering, Medical physics, Biomedical engineering, Image processing, Biomedical engineering / Medical engineering, Image Computing, Clinical data analysis, segmentation techniques, medical imaging algorithms, volume rendering applications, tomographic image reconstruction, machine learning for diagnostic imaging, spatial transformation methods
 

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