Main Page/SlicerCommunity/2019
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The community that relies on 3D Slicer is large and active: (numbers below updated on December 1st, 2023)
- 1,467,466+ downloads in the last 11 years (269,677 in 2023, 206,541 in 2022)
- over 17.900+ literature search results on Google Scholar
- 2,147+ papers on PubMed citing the Slicer platform paper
- Fedorov A., Beichel R., Kalpathy-Cramer J., Finet J., Fillion-Robin J-C., Pujol S., Bauer C., Jennings D., Fennessy F.M., Sonka M., Buatti J., Aylward S.R., Miller J.V., Pieper S., Kikinis R. 3D Slicer as an Image Computing Platform for the Quantitative Imaging Network. Magnetic Resonance Imaging. 2012 Nov;30(9):1323-41. PMID: 22770690. PMCID: PMC3466397.
- 39 events in open source hackathon series continuously running since 2005 with 3260 total participants
- Slicer Forum with +8,138 subscribers has approximately 275 posts every week
The following is a sample of the research performed using 3D Slicer outside of the group that develops it. in 2019
We monitor PubMed and related databases to update these lists, but if you know of other research related to the Slicer community that should be included here please email: marianna (at) bwh.harvard.edu.
2019
Morphological Analysis of Sigmoid Sinus Anatomy: Clinical Applications to Neurotological Surgery
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Publication: J Otolaryngol Head Neck Surg. 2019 Jan 11;48(1):2. PMID: 30635049 | PDF Authors: Van Osch K, Allen D, Gare B, Hudson TJ, Ladak H, Agrawal SK. Institution: Schulich School of Medicine & Dentistry, Western University, London, Ontario, Canada. Abstract: OBJECTIVES: The primary objective of this study was to use high-resolution micro-CT images to create accurate three-dimensional (3D) models of several intratemporal structures, and to compare several surgically important dimensions within the temporal bone. The secondary objective was to create a statistical shape model (SSM) of a dominant and non-dominant sigmoid sinus (SS) to provide a template for automated segmentation algorithms. METHODS: A free image processing software, 3D Slicer, was utilized to create three-dimensional reconstructions of the SS, jugular bulb (JB), facial nerve (FN), and external auditory canal (EAC) from micro-CT scans. The models were used to compare several clinically important dimensions between the dominant and non-dominant SS. Anatomic variability of the SS was also analyzed using SSMs generated using the Statismo software framework. RESULTS: Three-dimensional models from 38 temporal bones were generated and analyzed. Right dominance was observed in 74% of the paired SSs. All distances were significantly shorter on the dominant side (p < 0.05), including: EAC - SS (dominant: 13.7 ± 3.4 mm; non-dominant: 15.3 ± 2.7 mm), FN - SS (dominant: 7.2 ± 1.8 mm; non-dominant: 8.1 ± 2.3 mm), 2nd genu FN - superior tip of JB (dominant: 8.7 ± 2.2 mm; non-dominant: 11.2 ± 2.6 mm), horizontal distance between the superior tip of JB - descending FN (dominant: 9.5 ± 2.3 mm; non-dominant: 13.2 ± 3.5 mm), and horizontal distance between the FN at the stylomastoid foramen - JB (dominant: 5.4 ± 2.2 mm; non-dominant: 7.7 ± 2.1). Analysis of the SSMs indicated that SS morphology is most variable at its junction with the transverse sinus, and least variable at the JB. CONCLUSIONS: This is the first known study to investigate the anatomical variation and relationships of the SS using high resolution scans, 3D models and statistical shape analysis. This analysis seeks to guide neurotological surgical approaches and provide a template for automated segmentation and surgical simulation. "In 3D Slicer, nine fiducials (F1 – F9) were placed on the 3D reconstructions of the SS, JB, EAC, and FN to analyze several surgically relevant relationships between these structures." Funding:
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