Digital Anatomy: Applications of Virtual, Mixed and Augmented Reality

Description

This book offers readers fresh insights on applying Extended Reality to Digital Anatomy, a novel emerging discipline. Indeed, the way professors teach anatomy in classrooms is changing rapidly as novel technology-based approaches become ever more accessible. Recent studies show that Virtual (VR), Augmented (AR), and Mixed-Reality (MR) can improve both retention and learning outcomes.  Readers will find relevant tutorials about three-dimensional reconstruction techniques to perform virtual dissections. Several chapters serve as practical manuals for students and trainers in anatomy to refresh or develop their Digital Anatomy skills. We developed this book as a support tool for collaborative efforts around Digital Anatomy, especially in distance learning, international and interdisciplinary contexts. We aim to leverage source material in this book to support new Digital Anatomy courses and syllabi in interdepartmental, interdisciplinary collaborations.  Digital Anatomy – Applications of Virtual, Mixed and Augmented Reality provides a valuable tool to foster cross-disciplinary dialogues between anatomists, surgeons, radiologists, clinicians, computer scientists, course designers, and industry practitioners. It is the result of a multidisciplinary exercise and will undoubtedly catalyze new specialties and collaborative Master and Doctoral level courses world-wide. In this perspective, the UNESCO Chair in digital anatomy was created at the Paris Descartes University in 2015 (www.anatomieunesco.org). It aims to federate the education of anatomy around university partners from all over the world, wishing to use these new 3D modeling techniques of the human body. Foreword by Mark Billinghurst Foreword by Nicholas Ayache Acknowledgments Contents 1 Introduction to Digital Anatomy 1.1 From Dissection to Digital Anatomy 1.2 Imaging and Reconstruction 1.3 Virtual and Augmented Reality and Applications 1.4 Digital Anatomy as an Educational Tool References 2 From Anatomical to Digital Dissection: A Historical Perspective Since Antiquity Towards the Twenty-First Century 2.1 The Birth of Anatomy: The Knowledge of the Human Body from Antiquity to the Middle Ages 2.2 The Anatomical Evolution: Scientific Dissections During Renaissance and Enlightenment 2.3 The Clinic Meets Anatomy: Expansion of Anatomy in the Eighteenth and Nineteenth Centuries 2.4 New Perspectives: Anatomical Knowledge and Technical Evolution in the Twentieth Century 2.5 Modern Surgery: Twenty-First Century Anatomy in the Operating Theater 2.6 Anatomy 2020: What is the Place of Anatomy Today? 2.7 Anatomy in the Age of Virtual, Mixed, Augmented Reality: Twenty-First Century Digital Dissections 2.8 Future Directions in Digital Anatomy: Twenty-First Century as a Stage of Innovative Virtual Dissections References 3 A Tool for Collaborative Anatomical Dissection 3.1 Introduction 3.2 Related Work 3.3 Anatomy Studio 3.4 Evaluation 3.5 Results and Discussion 3.6 Lessons Learned 3.7 Conclusions References 4 3D Modeling from Anatomical and Histological Slices: Methodology and Results of Computer-Assisted Anatomical Dissection 4.1 Introduction 4.2 Materials and Methods 4.3 Results 4.4 Discussion 4.4.1 Limitations of the CAAD Technique 4.5 Conclusion References 5 Volume Rendering Technique from DICOM® Data Applied to the Study of Virtual Anatomy 5.1 Introduction 5.2 What Is a DICOM® Data? 5.3 What is a Volume Rendering Technique? 5.3.1 MDCT Volume Rendering Technique 5.4 Reconstruction Methods 5.4.1 Automatic Reconstruction Method 5.4.2 Semi-automatic Reconstruction Method 5.4.3 Manual Reconstruction Method 5.5 VRT Tools 5.5.1 Hounsfield Scale 5.5.2 Threshold 5.5.3 Automatic Tissue Removal 5.5.4 Smart Injection 5.5.5 Target Volume 5.5.6 Tissue Management 5.6 VRT Applied in MDCT Venography 5.6.1 PMDCT Protocols 5.6.2 PMDCT Enriched Rendered Volume (ERV) 5.7 Discussion 5.8 Conclusion References 6 The Virtual Dissection Table: A 3D Atlas of the Human Body Using Vectorial Modeling from Anatomical Slices 6.1 Introduction 6.2 History of the Visible Human Projects 6.3 Virtual Reality Techniques: A New Human–Computer Interface for Education 6.3.1 Objectives 6.3.2 Materials and Methods 6.4 Conclusion References 7 Segmentation and 3D Printing of Anatomical Models from CT Angiograms 7.1 Introduction 7.2 Objectives 7.3 Materials and Methods 7.3.1 3D Model Creation 7.3.2 3D Printing 7.3.3 Abdominal Aorta 3D Modeling and Printing 7.4 Discussion 7.5 Conclusion References 8 3D Reconstruction from CT Images Using Free Software Tools 8.1 3D Reconstruction Pipeline 8.2 3D Reconstruction of Subject-Specific Anatomical Structures 8.3 Conclusions References 9 Statistical Analysis of Organs' Shapes and Deformations: The Riemannian and the Affine Settings in Computational Anatomy 9.1 Introduction 9.1.1 Riemannian Manifolds 9.1.2 Statistics on Riemannian Manifolds 9.2 An Affine Symmetric Space Structure for Lie Groups 9.2.1 Affine Geodesics 9.2.2 An Affine Symmetric Space Structure for Lie Groups 9.2.3 Statistics in Affine Connection Spaces 9.2.4 The Case of Lie Groups with the Canonical Cartan–Schouten Connection 9.3 The SVF Framework for Shape and Deformation Modeling 9.3.1 Diffeomorphisms Parametrized by Stationary Velocity Fields 9.3.2 SVF-Based Diffeomorphic Registration with the Log-Demons 9.4 Modeling Longitudinal Deformation Trajectories in Alzheimer's Disease 9.4.1 Parallel Transport in Riemannian and Affine Spaces 9.4.2 Longitudinal Modeling of Alzheimer's Progression 9.5 The SVF Framework for Cardiac Motion Analysis 9.5.1 Parametric Diffeomorphisms with Locally Affine Transformations 9.5.2 Toward Intelligible Population-Based Cardiac Motion Features 9.6 Conclusion References 10 High Fidelity 3D Anatomical Visualization of the Fibre Bundles of the Muscles of Facial Expression as In situ 10.1 Introduction 10.2 Methods 10.3 Results 10.4 Discussion 10.5 Conclusions References 11 Collaborative VR Simulation for Radiation Therapy Education 11.1 Introduction 11.2 Background 11.3 LINACVR for Radiation Therapy Education 11.3.1 User Interface 11.3.2 Implementation and Architecture 11.4 Evaluation 11.5 Results 11.5.1 Quantitative Data 11.5.2 Question 1: What differences did you notice between this simulation and the real-world LINAC environment? 11.5.3 Question 2: How did this application compare to any other LINAC simulation programs you have used (e.g., VERT)? 11.5.4 Question 3: Are there any improvements you think could be made to this VR simulation? 11.5.5 Question 4: Do you have any other feedback about the simulation that you would like to give? 11.6 Discussion 11.7 Conclusions References 12 Multi-Touch Surfaces and Patient-Specific Data 12.1 Motivation and Background 12.1.1 Medical Application Scenarios 12.1.2 Science Communication Scenarios 12.2 Data Acquisition 12.3 Rendering Volumetric Data 12.3.1 Volume Raycasting 12.3.2 Transfer Function 12.4 Touch Interaction with Patient-Specific Volumetric Data 12.4.1 Case: Visualization Table for Medical Education 12.4.2 Case: Visualization Table for Science Communication 12.5 Summary and Conclusions References 13 Innovations in Microscopic Neurosurgery 13.1 The Neurosurgical Microscope from Past to Present 13.2 Robotic Applications for Neurosurgical Microscopes 13.3 High-Definition Exoscopes as Emerging Alternative 13.4 Augmented Reality in Neurosurgery 13.5 Hyperscope–Conceptualizing a Modern Visualization Tool for Neurosurgeons Integrating Exoscope, Endoscope, and Navigation in One System 13.6 Conclusion References 14 Simulating Cataracts in Virtual Reality 14.1 Introduction 14.2 Human Vision and Impairments 14.2.1 Understanding Visual Acuity 14.2.2 Impacts on Vision in VR Headsets 14.2.3 Cataracts 14.3 Related Work on Simulating Vision Impairments 14.3.1 Goggles 14.3.2 2D Images 14.3.3 3D Simulations 14.3.4 Virtual Reality Simulations 14.3.5 AR Simulations 14.4 Building an Effects Pipeline for Complex Eye Disease Patterns 14.4.1 Reduce Visual Acuity 14.4.2 Reduce Contrast 14.4.3 Apply Color Shift 14.4.4 Simulate Dark Shadows 14.4.5 Simulate Sensitivity to Light 14.4.6 Gaze-Dependent Effects 14.5 Calibrating Effects for Different Users and Hardware Devices 14.5.1 Vision Capabilities of Users 14.5.2 Calibration Methodology 14.5.3 Calibrating Reduced Visual Acuity 14.5.4 Calibrating Reduced Contrast 14.5.5 Order of Effects 14.6 Summary References 15 Patient-Specific Anatomy: The New Area of Anatomy Based on 3D Modelling 15.1 Introduction 15.2 Materials and Methods 15.3 Results 15.4 Discussion and Conclusion References 16 Virtual and Augmented Reality for Educational Anatomy 16.1 Introduction 16.2 Fundamentals of VR and AR in Medical Education 16.2.1 Learning Theoretical Foundations 16.2.2 Model Generation 16.3 AR in Anatomy Education 16.3.1 AR in Medicine 16.3.2 AR in Education 16.3.3 Mobile AR in Anatomy Education 16.3.4 Interaction 16.3.5 Anatomy Education 16.4 VR in Anatomy Education 16.4.1 Semi-Immersive VR 16.4.2 Immersive VR 16.4.3 VR for Specific Anatomical Regions 16.5 Concluding Remarks References 17 The Road to Birth: Using Digital Technology to Visualise Pregnancy Anatomy 17.1 Introduction 17.2 The Road to Birth 17.3 A Collaborative Design Approach 17.4 Immersive Virtual Reality (IVR) 17.5 Mobile Health (SPT) 17.6 Interaction Design and Approach 17.7 Initial Testing and Evaluation 17.8 Discussion 17.9 Conclusion References 18 Toward Constructivist Approach Using Virtual Reality in Anatomy Education 18.1 Introduction 18.2 Background and Prior Research 18.2.1 Challenges in Traditional Anatomy Education 18.2.2 Prior Research 18.2.3 Constructivist Approaches in Anatomy Education 18.2.4 Immersive Applications in Anatomy Education 18.3 Case Study One: Anatomy Builder VR 18.3.1 Overview of Anatomy Builder VR 18.3.2 Development of Anatomy Builder VR 18.3.3 Interaction Tasks in Anatomy Builder VR 18.3.4 User Study 18.4 Case Study TWO: Muscle Action VR 18.4.1 Overview of Muscle Action VR 18.4.2 Development of Muscle Action VR 18.4.3 User Experiences in Muscle Action VR 18.5 Conclusion References 19 A Study of Mobile Augmented Reality for Motor Nerve Deficits in Anatomy Education 19.1 Introduction 19.2 Background 19.2.1 Visual-Spatial Ability and Critical Thinking for Deeper Anatomy Knowledge 19.2.2 Mobile Devices and Augmented Reality for Personalized Anatomy Education 19.2.3 Existing User Interfaces in AR 19.3 Application: InNervate AR 19.3.1 Design 19.3.2 Key Elements of Design 19.3.3 Development 19.3.4 Learning Objectives 19.4 User Study 19.4.1 Participants Recruitment 19.4.2 Study Procedure 19.4.3 Data Collection to Measure Application Effectiveness 19.4.4 Data Analysis 19.5 Results & Discussion 19.5.1 Participant Demographics 19.5.2 Participant Crystal Slicing Test Results 19.5.3 Participant Test of Logical Thinking Results 19.5.4 Participant Anatomical Knowledge Scores Results 19.5.5 User Experience with InNervate AR 19.5.6 User Interface Analysis 19.6 Conclusions and Summary References