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Wallner J, Hochegger K, Chen X, Mischak I, Reinbacher K, Pau M, Zrnc T, Schwenzer-Zimmerer K, Zemann W, Schmalstieg D, Egger J. Clinical evaluation of semi-automatic open-source algorithmic software segmentation of the mandibular bone: Practical feasibility and assessment of a new course of action. PLoS One 2018; 13:e0196378. [PMID: 29746490 PMCID: PMC5944980 DOI: 10.1371/journal.pone.0196378] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2016] [Accepted: 04/12/2018] [Indexed: 11/19/2022] Open
Abstract
INTRODUCTION Computer assisted technologies based on algorithmic software segmentation are an increasing topic of interest in complex surgical cases. However-due to functional instability, time consuming software processes, personnel resources or licensed-based financial costs many segmentation processes are often outsourced from clinical centers to third parties and the industry. Therefore, the aim of this trial was to assess the practical feasibility of an easy available, functional stable and licensed-free segmentation approach to be used in the clinical practice. MATERIAL AND METHODS In this retrospective, randomized, controlled trail the accuracy and accordance of the open-source based segmentation algorithm GrowCut was assessed through the comparison to the manually generated ground truth of the same anatomy using 10 CT lower jaw data-sets from the clinical routine. Assessment parameters were the segmentation time, the volume, the voxel number, the Dice Score and the Hausdorff distance. RESULTS Overall semi-automatic GrowCut segmentation times were about one minute. Mean Dice Score values of over 85% and Hausdorff Distances below 33.5 voxel could be achieved between the algorithmic GrowCut-based segmentations and the manual generated ground truth schemes. Statistical differences between the assessment parameters were not significant (p<0.05) and correlation coefficients were close to the value one (r > 0.94) for any of the comparison made between the two groups. DISCUSSION Complete functional stable and time saving segmentations with high accuracy and high positive correlation could be performed by the presented interactive open-source based approach. In the cranio-maxillofacial complex the used method could represent an algorithmic alternative for image-based segmentation in the clinical practice for e.g. surgical treatment planning or visualization of postoperative results and offers several advantages. Due to an open-source basis the used method could be further developed by other groups or specialists. Systematic comparisons to other segmentation approaches or with a greater data amount are areas of future works.
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Affiliation(s)
- Jürgen Wallner
- Department of Oral & Maxillofacial Surgery, Medical University of Graz, Auenbruggerplatz 5/1, Graz, Austria
- Computer Algorithms for Medicine (Cafe) Laboratory, Graz, Austria
| | - Kerstin Hochegger
- Computer Algorithms for Medicine (Cafe) Laboratory, Graz, Austria
- Institute for Computer Graphics and Vision, Graz University of Technology, Inffeldgasse 16c/II, Graz, Austria
| | - Xiaojun Chen
- School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Irene Mischak
- Department of Dental Medicine and Oral Health, Medical University of Graz, Billrothgasse 4, Graz, Austria
| | - Knut Reinbacher
- Department of Oral & Maxillofacial Surgery, Medical University of Graz, Auenbruggerplatz 5/1, Graz, Austria
| | - Mauro Pau
- Department of Oral & Maxillofacial Surgery, Medical University of Graz, Auenbruggerplatz 5/1, Graz, Austria
| | - Tomislav Zrnc
- Department of Oral & Maxillofacial Surgery, Medical University of Graz, Auenbruggerplatz 5/1, Graz, Austria
| | - Katja Schwenzer-Zimmerer
- Department of Oral & Maxillofacial Surgery, Medical University of Graz, Auenbruggerplatz 5/1, Graz, Austria
| | - Wolfgang Zemann
- Department of Oral & Maxillofacial Surgery, Medical University of Graz, Auenbruggerplatz 5/1, Graz, Austria
| | - Dieter Schmalstieg
- Institute for Computer Graphics and Vision, Graz University of Technology, Inffeldgasse 16c/II, Graz, Austria
| | - Jan Egger
- Computer Algorithms for Medicine (Cafe) Laboratory, Graz, Austria
- Institute for Computer Graphics and Vision, Graz University of Technology, Inffeldgasse 16c/II, Graz, Austria
- BioTechMed-Graz, Krenngasse 37/1, Graz, Austria
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