Personalized, relevance-based Multimodal Robotic Imaging and augmented reality for Computer Assisted Interventions
Navab N, Hennersperger C, Frisch B, Furst B (2016)
Publication Type: Journal article
Publication year: 2016
Journal
Book Volume: 33
Pages Range: 64-71
DOI: 10.1016/j.media.2016.06.021
Abstract
In the last decade, many researchers in medical image computing and computer assisted interventions across the world focused on the development of the Virtual Physiological Human (VPH), aiming at changing the practice of medicine from classification and treatment of diseases to that of modeling and treating patients. These projects resulted in major advancements in segmentation, registration, morphological, physiological and biomechanical modeling based on state of art medical imaging as well as other sensory data. However, a major issue which has not yet come into the focus is personalizing intra-operative imaging, allowing for optimal treatment. In this paper, we discuss the personalization of imaging and visualization process with particular focus on satisfying the challenging requirements of computer assisted interventions. We discuss such requirements and review a series of scientific contributions made by our research team to tackle some of these major challenges.
Involved external institutions
Germany (DE)How to cite
APA:
Navab, N., Hennersperger, C., Frisch, B., & Furst, B. (2016). Personalized, relevance-based Multimodal Robotic Imaging and augmented reality for Computer Assisted Interventions. Medical Image Analysis, 33, 64-71. https://doi.org/10.1016/j.media.2016.06.021
MLA:
Navab, Nassir, et al. "Personalized, relevance-based Multimodal Robotic Imaging and augmented reality for Computer Assisted Interventions." Medical Image Analysis 33 (2016): 64-71.
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