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Medical Image Processing, Reconstruction and Restoration: Concepts and Methods

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Medical imaging is specific in that it concerns internal structures of organisms that are inaccessible to common imaging methods and that the imaging results are observed, evaluated, and classified mostly by non-technical staff. Development of new image processing methods and the interpretation of complicated or unexpected results require deep understanding of the underlying theory and methods involved in image processing and analysis. The author of this text provides a firm grounding in the principles as well as insight into the way of treating the image material. This book provides readers with consistent reasoning based on a firm grasp of image processing fundamentals, preferring the continuous well understandable explanation rather than strict mathematical formalism.

Beginning with modest initial attempts in roughly the 1960s, digital image processing has become a recognized field of science, as well
as a broadly accepted methodology, to solve practical problems in many different kinds of human activities. The applications encompass
an enormous range, starting perhaps with astronomy, geology, and physics, via medical, biological, and ecological imaging and
technological exploitation, up to the initially unexpected use in humane sciences, e.g., archaeology or art history. The results
obtained in the area of digital image acquisition, synthesis, processing, and analysis are impressive, though it is often not generally
known that digital methods have been applied. The basic concepts and theory are, of course, common to the spectrum of applications,
but some aspects are more emphasized and some less in each particular application field. This book, besides introducing general principles
and methods, concentrates on applications in the field of medical imaging, which is specific for at least two features: biomedical
imaging often concerns internal structures of living organisms inaccessible to standard imaging methods, and the resulting images
are observed, evaluated, and classified mostly by nontechnically oriented staff.

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