Methodology for Image-driven High-resolution Additive Manufacturing Using Discretized Data Set

Henry Oliver T. Ware, Wenzhong Liu, Jianmin Hu, Hao F Zhang, Cheng Sun*

*Corresponding author for this work

Research output: Contribution to journalConference article

Abstract

Additive manufacturing of patient-specific biomedical devices from 3D medical scans involves several steps of conversion which can introduce error into the final part. This is particularly critical to the fabrication of minute anatomical features, such as microvasculature. We show a direct conversion of the raw optical coherence tomography (OCT) volumetric data into photomasks in bitmap format, which streamlines the typical process steps used in 3D printing medical scans. OCT scans of rodent retinal microvasculature and projection microstereolithography are used to fabricate a solid vascular replica and a solid volume with hollow embedded microvessels.

Original languageEnglish (US)
Pages (from-to)139-144
Number of pages6
JournalProcedia CIRP
Volume65
DOIs
StatePublished - Jan 1 2017
Event3rd CIRP Conference on BioManufacturing 2017 - Chicago, United States
Duration: Jul 11 2017Jul 14 2017

Fingerprint

3D printers
Optical tomography
Photomasks
Printing
Fabrication

Keywords

  • 3D Printing
  • Optical Coherence Tomography
  • Projection microstereolithography
  • microvasculature

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering

Cite this

Ware, Henry Oliver T. ; Liu, Wenzhong ; Hu, Jianmin ; Zhang, Hao F ; Sun, Cheng. / Methodology for Image-driven High-resolution Additive Manufacturing Using Discretized Data Set. In: Procedia CIRP. 2017 ; Vol. 65. pp. 139-144.
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Methodology for Image-driven High-resolution Additive Manufacturing Using Discretized Data Set. / Ware, Henry Oliver T.; Liu, Wenzhong; Hu, Jianmin; Zhang, Hao F; Sun, Cheng.

In: Procedia CIRP, Vol. 65, 01.01.2017, p. 139-144.

Research output: Contribution to journalConference article

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