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(R)/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
- Includes advice for python and C++ users
- 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.
