Slice and Dice: A Physicalization Workflow for Anatomical Edutainment

During the last decades, anatomy has become an interesting topic in education—even for laymen or schoolchildren. As medical imaging techniques become increasingly sophisticated, virtual anatomical education applications have emerged. Still, anatomical models are often preferred, as they facilitate 3...

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Bibliographic Details
Published in:Computer graphics forum Vol. 39; no. 7; pp. 623 - 634
Main Authors: Raidou, Renata G., Gröller, M. Eduard, Wu, Hsiang‐Yun
Format: Journal Article
Language:English
Published: Oxford Blackwell Publishing Ltd 01.10.2020
Subjects:
Algorithms
Annotations
Applied computing ŕ Life and medical sciences
Assembly
CCS Concepts
Education
Finite element method
Human‐centered computing ŕ Visualization application domains
Imaging techniques
Medical imaging
Octrees
Optimization
Statuary
Three dimensional printing
Workflow
ISSN:0167-7055, 1467-8659
Online Access:Get full text
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Summary:During the last decades, anatomy has become an interesting topic in education—even for laymen or schoolchildren. As medical imaging techniques become increasingly sophisticated, virtual anatomical education applications have emerged. Still, anatomical models are often preferred, as they facilitate 3D localization of anatomical structures. Recently, data physicalizations (i.e., physical visualizations) have proven to be effective and engaging—sometimes, even more than their virtual counterparts. So far, medical data physicalizations involve mainly 3D printing, which is still expensive and cumbersome. We investigate alternative forms of physicalizations, which use readily available technologies (home printers) and inexpensive materials (paper or semi‐transparent films) to generate crafts for anatomical edutainment. To the best of our knowledge, this is the first computer‐generated crafting approach within an anatomical edutainment context. Our approach follows a cost‐effective, simple, and easy‐to‐employ workflow, resulting in assemblable data sculptures (i.e., semi‐transparent sliceforms). It primarily supports volumetric data (such as CT or MRI), but mesh data can also be imported. An octree slices the imported volume and an optimization step simplifies the slice configuration, proposing the optimal order for easy assembly. A packing algorithm places the resulting slices with their labels, annotations, and assembly instructions on a paper or transparent film of user‐selected size, to be printed, assembled into a sliceform, and explored. We conducted two user studies to assess our approach, demonstrating that it is an initial positive step towards the successful creation of interactive and engaging anatomical physicalizations.
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ISSN:0167-7055
1467-8659
DOI:10.1111/cgf.14173