This chapter is dedicated to educational applications of medical visualization techniques. Interactive 3D visualizations have great potential for anatomy education as well as for surgery education, with users ranging from high school students and physiotherapists to medical doctors who want to rehearse therapeutical interventions. Computer-assisted training systems enhance surgical manuals, surgical courses, and cadaver studies by providing up-to-date multimedia content. In particular

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... systems with self-assessment tools support problem-oriented learning and thus potentially improve problem-solving capabilities. Recent advances include web-based systems that enable personalized access with an individual profile and a list of favorite entries, as well as possibilities to upload content and discuss with colleagues. Among the potential users, case-based e-learning and interactive use of 3D models have also gained reasonable acceptance. In a recent survey, the majority of 176 German medical students answered that they like using such systems for educational purposes and for preparing exams [Birr et al., 2013]. In the same survey, it turned out that most multimedia systems based on canned drawings are criticized because of their low level of interactivity. However, the actual experience of medical students with interactive 3D visualizations is low. Thus, carefully designed and easy-to-use systems are required to stimulate the proliferation of educational systems based on interactive 3D visualizations. The Role of Visualization Techniques While advanced visualization techniques currently play only a minor role, they have the potential to enhance the display of complex interventions. Among the few systems having adopted advanced visualization techniques at an early stage is theVOXELMAN, an anatomy education system that even gave rise to the development of new visualization techniques, such as high-quality rendering at subvoxel accuracy and advanced vessel visualization. Surgical Simulators The most complex systems targeting on medical education are surgical simulators that aim at providing a realistic virtual environment for practicing complex surgical interventions. Many challenging tasks have to be solved to provide a convincing environment: Force feedback when tissue is touched or penetrated, collision detection, soft tissue deformation, cutting, and the simulation of various complications.We discuss these problems and focus on the interactive visualization techniques used in these settings. In addition, we discuss the design of such systems, the selection and structure of the underlying content and aspects of validation. In particular, the assessment of skills acquired with a training system, and the relevance of the acquired skills for clinical practice, have gained much attention in recent years. Increasingly, simulators are also employed for catheter-based interventions, where assistant doctors have to learn the selection of catheters and their deployment for complex vascular interventions. These interventions have many advantages for the patient, including reduced trauma and postoperative pain, but they exhibit inherent problems and pitfalls for the surgeon due to the small size of the incision through which all actions have to be performed. These problems include the lack of dexterity due to the loss of two degrees of freedom (instruments can only be moved forward or backward), the lack of fine-manipulation, and the degradation of force feedback in the interaction with human tissue which is Visual Computing for Medicine, Second Edition. http://dx.essential for the palpation of the patient [Tavakoli et al., 2006]. We describe some of the general problems, such as modeling elastic tissue properties, collision detection, simulating soft tissue deformation, and adequate force feedback. We primarily discuss applications in anatomy, interventional radiology, and different surgical disciplines. This is motivated by the benefit of interactive rendering of volume data and derived 3D models in these areas. Computer support may enhance education in selected medical disciplines. However, traditional forms of learning, such as lectures, and dissections of cadavers or physical models, as well as giving assistance during surgical interventions, shall not be replaced by any software solution. Training with Physical Models Another recent trend is the use of physical models derived from medical image data and produced with rapid prototyping technology. Segmentation and surface extraction are two essential steps related to the topic of this book. Due to progress in manufacturing technology, physical models are becoming much more affordable and at the same increasingly flexible with respect to the materials used. The great potential of physical models is that they may represent a variety of pathologies and enable the use of real surgical instruments.The emerging use of physical models is primarily motivated by the shortage of cadavers available for surgical training. Organization As a basis for the discussion of case studies, we introduce general concepts of computer-based training ( § 21.2) and metaphors for educational systems. Case studies in anatomy education ( § 21.3) and surgery education ( § 21.4) follow. The second part of the chapter is dedicated to systems that train procedures, instead of only presenting interactive multimedia content. This part starts with a discussion of the underlying techniques ( § 21.5), including haptics, collision detection, and soft tissue simulation. Case studies (simulation systems) in interventional radiology ( § 21.6) and surgery ( § 21.7) follow. We introduce simulation technology that employs rapid prototyping to enable training with physical models ( § 21.8). Finally, we discuss skills assessment, that is, concepts and systems that assess what was learned using a computer-assisted training system ( § 21.9). e -L E A R N I N G I N M E D I C I N E e-learning systems in medicine have been used for almost 50 years [Owen et al., 1965]. Due to the widespread availability of suitable computers and enhanced use of the multimedia presentation capabilities, the interest and popularity of e-learning has grown in recent years. Many experiments showed that the combination of presenting knowledge simultaneously with audio and video materials increases the retention of knowledge considerably [Mehrabi et al., 2000]. Although the initial costs of e-learning development are considerable, these systems can be updated more flexibly compared to traditional media. Also, the mode of presentation used in state-of-the-art e-learning systems is considered to be superior. It turns out that the large majority considered e-learning as useful, as a substantial help in self-study and exam preparation. In recent years, this also lead to broad acceptance of such education systems. Chittaro and Ranon [2007] further elaborate on the pedagogical motivation, in particular of interactive 3D visualization. Constructivism is a fundamental pedagogical theory according to which learning primarily occurs if trainees are "engaged in meaningful tasks." According to this theory, when we interact with an environment (a real or simulated environment), this enables direct, even unconscious experience and thus an increased depth of experience compared to, e.g., learning from listening to a teacher or reading a textbook. In essence, we construct the knowledge as learners ourselves. Among 21.2 e -L E A R N I N G I N M E D I C I N E e103 the medical education system explicitly mentioning constructivism as guiding theory is the anatomy teaching system ZYGOTE BODY [Kelc, 2012]. Another relevant concept of pedagogic theory is situated learning-a concept where learning experiences are provided in a context that is very similar to situations where this knowledge should be applied. Thus, surgery simulation or surgery training with physical models and real surgical instruments represents a setting where situated learning is possible. For education in medicine, an advantage of e-learning is that clinical pictures are represented graphically. Constructivism and Situated Learning Learning Objectives General concepts and rules of thumb for e-learning systems should be considered in the design and evaluation of educational systems for anatomy and surgery. e-learning systems should be based on a clear understanding of learning objectives and the target user group. The processes to acquire this understanding are known as task analysis and audience analysis [Lee and Owens, 2000] (recall Chap. 5). The design of e-learning systems is a special aspect of interactive system design. Therefore, textbooks on this topic, such as [Shneiderman and Plaisant, 2009] are relevant here. In particular, the scenario-based approach to user interface design, advocated by Rosson and Carroll [2003], is highly recommended and has been proven successful in e-learning projects, such as the SPINESURGERYTRAINER [Kellermann et al., 2011] and the LIVERSURGERYTRAINER [Mönch et al., 2013].The core idea of this approach is that developers and users agree on essential scenarios, sequences of user input and system output described informally in natural language. These scenarios should guide the analysis stage, the prototyping activities, user evaluations as well as the documentation of interactive systems (recall § 5.2.3.2). e-learning systems should provide a self-steered and directed method of learning. With e-learning systems, users can"pick an individual learning pace" [Mehrabi et al., 2000]. A path to the learning environment that can be followed, left and re-entered freely, is necessary. It is essential that users can explore the material, for example by interrogating graphical representations, by answering multiple-choice questions or by solving tasks which involve a manipulation of graphical objects. Examples for learning objectives in anatomy are the following. Students should be able • to locate certain structures, • to know the functional relation between certain structures, and • to recognize typical variations of certain structures. Learning objectives should be explicitly specified, and they should guide the design and development of e-learning systems. The analysis and understanding of learning objectives may serve as a basis to guide the user and provide an appropriate learning experience. Success Criteria In summary, to enable successful learning, e-learning systems should: • provide realistic and appealing examples, • support active participation where users not only observe prepared sequences of images, textual description, and animation, but have to make decisions and to solve tasks, • provide adequate feedback, in particular when the user solved a task, • provide self-assessment tools, such as quizzes or multiple-choice questions, • allow the user a flexible exploration of tasks and material with navigation aids telling the user what has been done and what could be done next. Finally, the success of e-learning systems also depends on the motivation of learners. If the use of an e-learning system is perceived as diligent work only, few users will fully exploit its capabilities. The study of techniques from the area of computer games may help to get inspirations for combining learning with an entertainment experience. e-learning in Anatomy and Surgery In medicine cognitive and motor skills are important. Cognitive skills comprise factual knowledge, e.g., names of anatomical structures, and knowledge of procedures, e.g., the selection of a basic treatment, the steps to be performed, complications, follow-up and postoperative management. Motor skills comprise psychomotor skills to actually perform a procedure, e.g., to apply the right amount of pressure to insert a catheter in a vascular tree or to perform suturing and knot tying in laparoscopic surgery. Cognitive skills may be verified with a quiz or multiple-choice questionnaires [Oropesa et al., 2010]. The training of motor skills requires training systems which enable to practice the actual procedure. The assessment of motor skills is largely performed by observations from experts and by some automatic measures, related to dexterity. The assessment of motor skills is far less standardized compared to cognitive skills assessment [Oropesa et al., 2010]. e-learning systems for anatomy and surgery education focus on the acquisition of cognitive skills.They require appropriate image data and segmentation results. Based on these data, high-quality renderings can be generated and interactively explored as an essential component of such e-learning systems. Thus, in addition to the above-mentioned general requirements for e-learning systems in medicine, there are some further requirements for systems related to image data, e.g., in radiology and surgery.These systems should: • provide 2D visualizations with overlays representing segmentation results, • provide high-quality 3D models and related visualizations to explore spatial relations, e.g., margins and vascular supply areas, • provide integrated 2D and 3D visualization with synchronization, e.g., when objects are selected, • provide easy-to-use interaction facilities, such as incremental rotation. While clinical applications require fast segmentation and visualization, educational systems require primarily high-quality results. By the way, the accuracy of visualizations is less important. Smooth surfaces without distracting features are preferred. Datasets play a key role in medical education. High resolution datasets with a good signal-to-ratio and only few artifacts enable the detailed exploration of anatomical structures.The acquisition of such datasets requires considerable experience, appropriate infrastructure and thus is expensive. Fortunately, the best datasets are publicly available and triggered a boost of educational systems. Visible Human The most widely used data sources for anatomy education are the Visible Human datasets. These 3D datasets originate from two bodies that were given to science, frozen, and digitized into horizontally spaced slices. A total number of 1871 cryosection slices were generated for the Visible Man (1 mm slice distance) and even more for the Visible Woman (0.33 mm slice distance). Besides photographic cryosectional images, fresh and frozen CT data, as well as MR images, were acquired. The project was