Visualization, Visual Analytics and Virtual Reality in Medicine
State-of-the-art Techniques and Applications
- 1st Edition - May 15, 2023
- Imprint: Academic Press
- Authors: Bernhard Preim, Renata Raidou, Noeska Smit, Kai Lawonn
- Language: English
- Paperback ISBN:9 7 8 - 0 - 1 2 - 8 2 2 9 6 2 - 0
- eBook ISBN:9 7 8 - 0 - 1 2 - 8 2 3 1 0 6 - 7
Visualization, Visual Analytics and Virtual Reality in Medicine: State-of-the-art Techniques and Applications describes important techniques and applications that show an understan… Read more
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Request a sales quoteVisualization, Visual Analytics and Virtual Reality in Medicine: State-of-the-art Techniques and Applications describes important techniques and applications that show an understanding of actual user needs as well as technological possibilities. The book includes user research, for example, task and requirement analysis, visualization design and algorithmic ideas without going into the details of implementation. This reference will be suitable for researchers and students in visualization and visual analytics in medicine and healthcare, medical image analysis scientists and biomedical engineers in general.
Visualization and visual analytics have become prevalent in public health and clinical medicine, medical flow visualization, multimodal medical visualization and virtual reality in medical education and rehabilitation. Relevant applications now include digital pathology, virtual anatomy and computer-assisted radiation treatment planning.
- Combines visualization, virtual reality and analytics
- Written by leading researchers in the field
- Gives the latest state-of-the-art techniques and applications
Researchers and graduate students in medical imaging and visualization
- Cover image
- Title page
- Table of Contents
- Copyright
- Preface
- Chapter 1: Introduction
- Abstract
- Acknowledgement
- References
- Part 1: Medical visualization techniques
- Introduction
- Chapter 2: Illustrative medical visualization
- Abstract
- 2.1. Introduction
- 2.2. Definition
- 2.3. Requirements
- 2.4. Preliminaries
- 2.5. Illustrative visualization techniques
- 2.6. Concluding remarks
- References
- Chapter 3: Advanced vessel visualization
- Abstract
- 3.1. Introduction
- 3.2. Perception-based vessel visualization
- 3.3. Integrated visualization of vascular surfaces and embedded flow
- 3.4. Focus-and-context vessel visualization
- 3.5. Vessel visualization for diagnosis and treatment planning
- 3.6. Concluding remarks
- References
- Chapter 4: Multimodal medical visualization
- Abstract
- 4.1. Introduction
- 4.2. Medical imaging modalities
- 4.3. Workflow and requirements
- 4.4. Visualization techniques
- 4.5. Rendering and interaction techniques
- 4.6. Selected applications
- 4.7. Concluding remarks
- References
- Chapter 5: Medical flow visualization
- Abstract
- 5.1. Introduction
- 5.2. Medical background of flow data generation
- 5.3. Generation of medical flow data
- 5.4. Task-based visual analysis of medical flow data
- 5.5. Medical flow analysis systems
- 5.6. Concluding remarks
- References
- Chapter 6: Medical animations
- Abstract
- 6.1. Introduction
- 6.2. Fundamentals
- 6.3. Medical animations of static data
- 6.4. Animated volume rendering
- 6.5. Medical animations of dynamic data
- 6.6. Applications of animations based on static data
- 6.7. Interactive animations
- 6.8. The process of animation generation
- 6.9. Concluding remarks
- References
- Part 2: Selected applications
- Introduction
- Chapter 7: 3D visualization for anatomy education
- Abstract
- 7.1. Introduction
- 7.2. Educational background
- 7.3. Datasets
- 7.4. Visualization techniques
- 7.5. Knowledge representation and labeling
- 7.6. Interaction techniques
- 7.7. Virtual anatomy systems
- 7.8. 3D web-based anatomy education
- 7.9. Evaluation of virtual anatomy systems
- 7.10. Concluding remarks
- References
- Chapter 8: Visual computing for radiation treatment planning
- Abstract
- 8.1. Introduction
- 8.2. Background on cancer
- 8.3. Radiation therapy (RT)
- 8.4. Definition of target volumes and organs at risk
- 8.5. Treatment plan design and dose calculation
- 8.6. Dose plan review and treatment evaluation
- 8.7. Image-guided adaptive RT
- 8.8. Concluding remarks
- References
- Part 3: Visual analytics in healthcare
- Introduction
- Chapter 9: An introduction to visual analytics
- Abstract
- 9.1. Introduction
- 9.2. The data–users–tasks design triangle
- 9.3. Information visualization
- 9.4. Statistical methods employed in visual analytics
- 9.5. Dimension reduction
- 9.6. Clustering
- 9.7. Subspace clustering
- 9.8. Association rule mining
- 9.9. Correlation-based visual analytics
- 9.10. Interaction
- 9.11. Challenges in visual analytics for clinical applications
- 9.12. Concluding remarks
- References
- Chapter 10: Visual analytics in public health
- Abstract
- 10.1. Introduction
- 10.2. Public health
- 10.3. Data for public health
- 10.4. Commonly used visual analytics techniques
- 10.5. Analysis and control of epidemics
- 10.6. Visual analytics for epidemiological research
- 10.7. Visual analytics of population-based cohort study data
- 10.8. Evaluation
- 10.9. Concluding remarks
- References
- Chapter 11: Visual analytics in clinical medicine
- Abstract
- 11.1. Introduction
- 11.2. Data in clinical medicine
- 11.3. Visual analytics of event-type data
- 11.4. Visualization of single patient data
- 11.5. Visualization of patient cohort data
- 11.6. Visual analytics for prediction
- 11.7. Clinical decision support
- 11.8. Selected applications
- 11.9. Concluding remarks
- References
- Part 4: Virtual Reality in medicine
- Introduction
- Chapter 12: Introduction to Virtual Reality
- Abstract
- 12.1. Introduction
- 12.2. Immersion and presence
- 12.3. VR sickness
- 12.4. VR hardware
- 12.5. Avatar design
- 12.6. Basic interaction techniques
- 12.7. Locomotion techniques
- 12.8. Haptics
- 12.9. Audio feedback
- 12.10. Applications
- 12.11. Concluding remarks
- References
- Chapter 13: Virtual Reality for medical education
- Abstract
- 13.1. Introduction
- 13.2. Collaborative Virtual Reality
- 13.3. VR for anatomy education
- 13.4. VR for surgery training
- 13.5. Concluding remarks
- References
- Chapter 14: Virtual Reality in treatment and rehabilitation
- Abstract
- 14.1. Introduction
- 14.2. Potential of gamification
- 14.3. VR-based pain management
- 14.4. VR exposure therapy for treatment of anxieties
- 14.5. VR for rehabilitation
- 14.6. Concluding remarks
- References
- References
- References
- Index
- Edition: 1
- Published: May 15, 2023
- Imprint: Academic Press
- No. of pages: 568
- Language: English
- Paperback ISBN: 9780128229620
- eBook ISBN: 9780128231067
BP
Bernhard Preim
Bernhard Preim was born in 1969 in Magdeburg, Germany. He received the diploma in computer science in 1994 (minor in mathematics) and a Ph.D. in 1998 for a thesis on interactive visualization for anatomy education from the Otto-von-Guericke University of Magdeburg. In 1999 he moved to Bremen where he joined the staff of MEVIS and directed the “computer-aided planning in liver surgery” group.
Since Mars 2003 he is full professor for Visualization at the computer science department at the Otto-von-Guericke-University of Magdeburg, heading a research group focussed on medical visualization.
His research interests include vessel visualization, exploration of blood flow, visual analytics in public health, virtual reality in medical education and since recently narrative visualization. He authored “Visualization in Medicine” (Co-author Dirk Bartz, 2007) and “Visual Computing in Medicine” (Co-author: C. Botha, 2013).
Bernhard Preim founded the working group Medical Visualization in the German Society for Computer Science and served as speaker from 2003-2012. He was president of the German Society for Computer- and Robot-Assisted Surgery (www.curac.org). He was Co-Chair and Co-Organizer of the first and second Eurographics Workshop on Visual Computing in Biology and Medicine (VCBM) in 2008 and 2010 and lead the steering committee of that workshop until 2019.
He is the chair of the scientific advisory board of ICCAS (International Competence Center on Computer-Assisted Surgery Leipzig, since 2010). From 2011-2018 he was an associate editor of IEEE Transactions on Medical Imaging and and IEEE Transactions on Visualization and Graphics (2017-2022). Currently he serves in the editorial board of Computers & Graphics (since 2019). He was also regularly a Visiting Professor at the University of Bremen where he closely collaborates with Fraunhofer MEVIS (2003-2012) and was Visiting Professor at TU Vienna (2016).
Affiliations and expertise
Professor of Visualization, Computer Science Department, Otto-von-Guericke-University of Magdeburg, GermanyRR
Renata Raidou
Renata Raidou is Assistant Professor in Medical Visualization and Visual Analytics at the Research Unit of Computer Graphics of the Institute of Visual Computing & Human-Centered Technology, at TU Wien, Austria.
Previously, she was Assistant Professor and Rosalind Franklin Fellow at the Scientific Visualization and Computer Graphics Research Group of the Bernoulli Institute at the University of Groningen, the Netherlands. She did her Post-Doc at the Institute of Visual Computing & Human-Centered Technology, at TU Wien. She received her Ph.D. in Medical Visualization from Eindhoven University of Technology, the Netherlands, in 2017. The topic of her dissertation was “Visual Analytics for Digital Radiotherapy: Towards a Comprehensible Pipeline”, and for the results of her work, she was awarded the Best Ph.D. Award 2018 of the EuroVis Awards Programme. Additionally, she received the Dirk Bartz Prize for Visual Computing in Medicine (1st Place) at Eurographics 2017, and in 2022 she was awarded the EuroVis Young Researcher Award.
Her research focus is on the interface between Visual Analytics, Image Processing, and Machine Learning, with a strong focus on medical applications—in particular, cancer radiotherapy. Her specific domains of expertise are Comparative Visual Analytics and Uncertainty Visualization. She is also interested in visualization topics revolving around biological and medical education.
Affiliations and expertise
Assistant Professor in Medical Visualization and Visual Analytics, Research Unit of Computer Graphics of the Institute of Visual Computing & Human-Centered Technology, TU Wien, Austria.NS
Noeska Smit
Noeska Smit was born in 1983 in Heenvliet, the Netherlands. She became a licensed radiographer in Rotterdam in 2005. Afterwards, she obtained her master’s in computer science with a minor in biomedical engineering in 2012 at the Delft University of Technology. At the same institute, she defended her PhD thesis on interactive visualization for anatomy education and surgical planning in 2016.
She moved to Bergen, Norway, to join the visualization research group at the Department of Informatics as a tenure-track Associate Professor in medical visualization in 2016. Since 2019, she holds a position as a senior researcher at the Mohn Medical Imaging and Visualization (MMIV) center at the Department of Radiology of the Haukeland University Hospital in Norway. She is part of the leadership team at this interdisciplinary center.
She leads a team researching multimodal medical data visualization. In her interdisciplinary research, she works on novel interactive visualization approaches for improved exploration, analysis, and communication of multimodal medical imaging data. Her work has been awarded with a Dirk Bartz prize for Visual Computing in Medicine in 2019 and the Best Interdisciplinary Presentation Award, awarded at the Computer Graphics International conference in 2020.
Affiliations and expertise
senior researcher, Mohn Medical Imaging and Visualization (MMIV) center, Department of Radiology of the Haukeland University Hospital, NorwayKL
Kai Lawonn
Kai Lawonn was born in 1985 in Berlin, Germany. He received the diploma in mathematics in 2011 (minor in physics) and a Ph.D. in 2014 for a thesis on illustrative visualization on medical data sets from the Otto-von-Guericke University of Magdeburg. In 2015 he moved to Koblenz where he become a Junior professor at the University of Koblenz-Landau for Medical Visualization.
In 2019 he moved to Jena, Germany, where he is now a full professor for Visualization and Explorative Data Analysis. His work on visualization was awarded with the Best Ph.D. Award 2016 of the Eurographics Awards Programme, the EuroVis Young Researcher Award in 2020, and the Heinz Maier-Leibnitz Prize in 2021.
His research interests include vessel visualization, exploration of blood flow, illustrative visualization, and since recently visualization of machine learning techniques.
Affiliations and expertise
Assistant Professor for visualization, University of Jena, GermanyRead Visualization, Visual Analytics and Virtual Reality in Medicine on ScienceDirect