| Title |
Pre-clinical validation of virtual bronchoscopy using 3D Slicer
|
|---|---|
| Published in |
International Journal of Computer Assisted Radiology and Surgery, June 2016
|
| DOI | 10.1007/s11548-016-1447-7 |
| Pubmed ID | |
| Authors |
Pietro Nardelli, Alexander Jaeger, Conor O’Shea, Kashif A. Khan, Marcus P. Kennedy, Pádraig Cantillon-Murphy |
| Abstract |
Lung cancer still represents the leading cause of cancer-related death, and the long-term survival rate remains low. Computed tomography (CT) is currently the most common imaging modality for lung diseases recognition. The purpose of this work was to develop a simple and easily accessible virtual bronchoscopy system to be coupled with a customized electromagnetic (EM) tracking system for navigation in the lung and which requires as little user interaction as possible, while maintaining high usability. The proposed method has been implemented as an extension to the open-source platform, 3D Slicer. It creates a virtual reconstruction of the airways starting from CT images for virtual navigation. It provides tools for pre-procedural planning and virtual navigation, and it has been optimized for use in combination with a [Formula: see text] of freedom EM tracking sensor. Performance of the algorithm has been evaluated in ex vivo and in vivo testing. During ex vivo testing, nine volunteer physicians tested the implemented algorithm to navigate three separate targets placed inside a breathing pig lung model. In general, the system proved easy to use and accurate in replicating the clinical setting and seemed to help choose the correct path without any previous experience or image analysis. Two separate animal studies confirmed technical feasibility and usability of the system. This work describes an easily accessible virtual bronchoscopy system for navigation in the lung. The system provides the user with a complete set of tools that facilitate navigation towards user-selected regions of interest. Results from ex vivo and in vivo studies showed that the system opens the way for potential future work with virtual navigation for safe and reliable airway disease diagnosis. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Ireland | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 50 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 8 | 16% |
| Student > Master | 6 | 12% |
| Student > Ph. D. Student | 5 | 10% |
| Student > Bachelor | 5 | 10% |
| Other | 4 | 8% |
| Other | 11 | 22% |
| Unknown | 11 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 11 | 22% |
| Engineering | 9 | 18% |
| Nursing and Health Professions | 3 | 6% |
| Computer Science | 3 | 6% |
| Psychology | 2 | 4% |
| Other | 9 | 18% |
| Unknown | 13 | 26% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 24 June 2016.
All research outputs
#15,379,002
of 22,879,161 outputs
Outputs from International Journal of Computer Assisted Radiology and Surgery
#497
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Outputs of similar age
#223,368
of 353,105 outputs
Outputs of similar age from International Journal of Computer Assisted Radiology and Surgery
#11
of 19 outputs
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