Article3D printing and additive manufacturing2022
Toward Emulating Human Movement: Adopting a Data-Driven Bitmap-Based "Voxel" Multimaterial Workflow to Create a Flexible 3D Printed Neonatal Lower Limb.
Article in 3D printing and additive manufacturing, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed, 4 citations in OpenAlex.
- Synthetic 3D printed tibial plateau with gradient material properties for biomechanical accuracy.Frontiers in bioengineering and biotechnology · 2025Article
- Thermomechanical Properties of Polyjet Voxel-Printed Parts and the Effect of Percolation.3D printing and additive manufacturing · 2024Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
It is increasingly common to produce physical anatomical medical models using high-fidelity multiproperty 3D printing to assist doctor-patient communication, presurgical planning, and surgical simulation. Currently, most medical models are created using image thresholding and traditional mesh-based segmentation techniques to produce mono-material boundaries (STL file formats) of anatomical features. Existing medical modeling manufacturing methods restrict shape specification to one material or density, which result in anatomically simple 3D printed medical models with no gradated material qualities. Currently, available high-resolution functionally graded multimaterial 3D printed medical models are rigid and do not represent biomechanical movement. To bypass the identified limitations of current 3D printing medical modeling workflows, we present a bitmap-based "voxel" multimaterial additive manufacturing workflow for the production of highly realistic and flexible anatomical models of the neonatal lower limb using computed tomographic ("CT") data. By interpolating and re-slicing a biomedical volumetric data set at the native 3D printer
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