Title
Nerves of Steel: a Low-Cost Method for 3D Printing the Cranial Nerves.
Abstract
Steady-state free precession (SSFP) magnetic resonance imaging (MRI) can demonstrate details down to the cranial nerve (CN) level. High-resolution three-dimensional (3D) visualization can now quickly be performed at the workstation. However, we are still limited by visualization on flat screens. The emerging technologies in rapid prototyping or 3D printing overcome this limitation. It comprises a variety of automated manufacturing techniques, which use virtual 3D data sets to fabricate solid forms in a layer-by-layer technique. The complex neuroanatomy of the CNs may be better understood and depicted by the use of highly customizable advanced 3D printed models. In this technical note, after manually perfecting the segmentation of each CN and brain stem on each SSFP-MRI image, initial 3D reconstruction was performed. The bony skull base was also reconstructed from computed tomography (CT) data. Autodesk 3D Studio Max, available through freeware student/educator license, was used to three-dimensionally trace the 3D reconstructed CNs in order to create smooth graphically designed CNs and to assure proper fitting of the CNs into their respective neural foramina and fissures. This model was then 3D printed with polyamide through a commercial online service. Two different methods are discussed for the key segmentation and 3D reconstruction steps, by either using professional commercial software, i.e., Materialise Mimics, or utilizing a combination of the widely available software Adobe Photoshop, as well as a freeware software, OsiriX Lite.
Year
DOI
Venue
2017
https://doi.org/10.1007/s10278-017-9951-z
J. Digital Imaging
Keywords
Field
DocType
3D model,3D printing,Anatomy,Cerebellopontine angle,Cranial nerve,Education,Radiology,Rapid prototyping,Simulation,Skull base,Surgical planning
Rapid prototyping,Computer graphics (images),Segmentation,Computer science,Visualization,Workstation,Commercial software,Software,3D printing,Radiology,3D reconstruction
Journal
Volume
Issue
ISSN
30
5
0897-1889
Citations 
PageRank 
References 
0
0.34
0
Authors
3
Name
Order
Citations
PageRank
Ramin Javan162.20
Duncan Davidson200.34
Afshin Javan300.34