Abstract
There has been a tremendous increase in medical image computing research and development over the last decade. This trend continues to gain further speed, driven by the sheer amount of multimodal medical image data but also by the broad spectrum of computer-assisted applications. At the same time, user expectations with respect to diagnostic accuracy, robustness, speed, automation, workflow efficiency, broad availability, as well as intuitive use have reached a high level already. More recently, cloud computing has entered the field of medical imaging, providing means for more flexible workflows including the support of mobile devices and even a medical imaging equivalent of the App Store paradigm. This paper discusses requirements for modern medical software systems with a focus on image analysis and visualization. It provides examples from different areas of application covering collaborative multi-center imaging trials with online reading and advanced analysis as well as an intraoperative augmented-reality scenario for translating liver surgery planning data directly into the operating room through a mobile multi-touch device. A combination of remote rendering and visualization techniques with an efficient modular development framework (MeVisLab) is presented as a basis for fast implementation, early evaluation, and iterative optimization in these applications.
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Kohlmann, P. et al. (2016). Remote Visualization Techniques for Medical Imaging Research and Image-Guided Procedures. In: Linsen, L., Hamann, B., Hege, HC. (eds) Visualization in Medicine and Life Sciences III. Mathematics and Visualization. Springer, Cham. https://doi.org/10.1007/978-3-319-24523-2_6
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