Preface to the First Edition

Given the rapid evolution of radiological imaging in the past four decades, medical image processing nowadays is an essential tool for clinical research. Applications range from research in neuroscience, biomechanics and biomedical engineering to clinical routine tasks such as the visualization of huge datasets provided by modern computed tomography systems in radiology, the manufacturing of patient-specific prostheses for orthopedic surgery, the precise planning of dose distributions in radiation oncology, the fusion of multimodal image data for therapy monitoring in internal medicine, and computer-aided neurosurgical interventions.

For more than a decade, we have been working as scientists in this vital field of research at various institutions and hospitals; and still, it is a fascinating subject. We have also taught the subject of medical image processing to undergraduate and graduate students of medical physics, biomedical engineering, medicine and computer science; our audience usually also was at least interested and some students even shared our sense of fascination.

However, besides our own enthusiasm, we always felt a little bit unsatisfied with the available textbooks on the subject of medical image processing. Some of them we found very formal, others were discontinuous due to the fact that they were written by a multitude of authors; some are not very useful as an introduction since they are too specialized, and a few are of little use at all.

On the other hand, there are a number of good introductions to image processing in general, but the requirements of the medical community differ in some important aspects; above all, we do not deal with images in a common sense since most of our imaging machines acquire their data outside the visual spectrum. Furthermore, many modern imaging methods are three-dimensional. The problems of handling voxels and 3D datasets, spatial transforms in 3D, and data fusion are usually not being dealt with to a sufficient extent in these works.

Based on our own experience, we came to the conclusion that an introductory textbook for undergraduate and first year Ph.D. students should have the following features:

It should give an overview of the relevant basic methods in applied medical image processing.

It should assume little prior knowledge beyond basic applied mathematics, physics and programming.

It should be tangible; rather than giving theoretic derivations, it would be nice to demonstrate how things work in real life.

It should be accessible. The use of expensive software or highly sophisticated programming techniques is to be avoided.

You hold the outcome of such an effort in your hands. Whether we met our own demands is to be judged by you. If you find errors – quite likely, there are a number of them – or if you have suggestions for improvement, we would be grateful if you would point those out to us. Have fun!

Wolfgang Birkfellner, Michael Figl, and Johann Hummel