Fig. 5 Curve and graph data processing workflows and their representative 3D-printed models. Curve and graph data processing workflows and their representative.

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Presentation transcript:

Fig. 5 Curve and graph data processing workflows and their representative 3D-printed models. Curve and graph data processing workflows and their representative 3D-printed models. For the input curve or graph data (A), an enclosure is specified (B) from which dimensions and number of printing layers are determined (C). (D) For each pixel in each layer, the closest curve or line segment is queried (E), and properties associated with the curve or line segments are interpolated and rasterized to the layer. (F) Every material information layer is dithered into binary material composition layers, one for each material that is needed to fabricate the input data set. (G) Protein crystal structure of apolipoprotein A-I. The data set consists of 6588 points (representing each atom) and 13,392 line segments, representing the interatomic bonds. (H) White matter tractography data of the human brain, created with the 3D Slicer medical image processing platform (37), visualizing bundles of axons, which connect different regions of the brain. The original data were acquired through diffusion-weighted MRI, where 48 scans are taken for each MRI slice, to capture the diffusion of water molecules in white matter brain tissue, which is visualized as 3595 individual fibers. The fiber data set consists of a total of 291,362 line segments that are colored according to their orientation in 3D space. Christoph Bader et al. Sci Adv 2018;4:eaas8652 Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC).