Guide to Medical Image Analysis

Medical images are different from other pictures in that they depict distributions of various physical features measured from the human body. They show attributes that are otherwise inaccessible. Furthermore, the analysis of such images is guided by very specific expectations, which gave rise to acquiring the images in the first place. This has consequences on the kind of analysis and on the requirements for algorithms that carry out some or all of the analysis. Image analysis as part of the clinical workflow will be discussed in this chapter as well as the types of tools that exist to support the development and carrying out of such an analysis. We will conclude with an example for the solution of an analysis task to illustrate important aspects for the development of methods for analyzing medical images. Concepts, notions and definitions introduced in this chapter › Introduction to basic development strategies › Common analysis tasks: delineation, object detection, and classification › Image analysis for clinical studies, diagnosis support, treatment planning, and computer-assisted therapy › Tool types: viewers, workstation software, and development tools Why is there a need for a book on medical image analysis when there are plenty of good texts on image analysis around? Medical images differ from photography in many ways. Consider the picture in Fig. 1.1 and the potential questions and problems related to its analysis. The first question that comes to mind would probably be to detect certain objects (e.g., persons). Common problems that have to be solved are to recover the three-dimensional (3D) information (i.e., missing depth information and the true shape) to separate illumination effects from object appearance, to deal with partially hidden objects, and to track objects over time. K.D. Toennies, Guide to Medical Image Analysis, Advances in Computer Vision and Pattern Recognition, DOI 10.1007/978-1-4471-2751-2_1, © Springer-Verlag London Limited 2012 1 2 1 The Analysis of Medical Images Fig. 1.1 Analysis questions for a photograph are often based on a detection or tracking task (such as detecting real persons in the image). Problems relate to reducing effects from the opacity of most depicted objects and to the reconstruction of depth information (real persons are different from those on the picture because they are 3D, and—if a sequence of images is present—because they can move) Medical images are different. Consider the image in Fig. 1.2. The appearance of the depicted object is not caused by light reflection, but from the absorption of x rays. The object is transparent with respect to the depicted physical attribute. Although the detection of some structure may be the goal of the analysis, the exact delineation of the object and its substructures may be the first task. The variation of the object shape and appearance may be characteristic for some evaluation and needs to be captured. Furthermore, this is not the only way to gain insight into the human body. Different imaging techniques produce mappings of several physical attributes in various ways that may be subjects of inspection (compare Fig. 1.2 with Fig. 1.3). Comparing this information with reality is difficult, however, since few if any noninvasive methods exist to verify the information gained from the pictures. Hence, the focus on analysis methods for medical images is different if compared to the analysis of many other images. Delineation, restoration, enhancement, and registration for fusing images from different sources are comparably more important than classification, reconstruction of 3D information, and tracking (although it does not mean that the last three topics are irrelevant for medical image analysis). This shift in focus is reflected in our book and leads to the following structure. • Medical images, their storage, and use will be discussed in Chaps. 2 and 3. • Enhancement techniques and feature computation will be the subject of Chaps. 4 and 5. • Delineation of object boundaries, finding objects and registering information from different sources will make up the majority of the book. It will be presented

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