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Erschienen in: International Journal of Computer Assisted Radiology and Surgery 2/2015

01.02.2015 | Original Article

PyDBS: an automated image processing workflow for deep brain stimulation surgery

verfasst von: Tiziano D’Albis, Claire Haegelen, Caroline Essert, Sara Fernández-Vidal, Florent Lalys, Pierre Jannin

Erschienen in: International Journal of Computer Assisted Radiology and Surgery | Ausgabe 2/2015

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Abstract

Purpose

   Deep brain stimulation (DBS) is a surgical procedure for treating motor-related neurological disorders. DBS clinical efficacy hinges on precise surgical planning and accurate electrode placement, which in turn call upon several image processing and visualization tasks, such as image registration, image segmentation, image fusion, and 3D visualization. These tasks are often performed by a heterogeneous set of software tools, which adopt differing formats and geometrical conventions and require patient-specific parameterization or interactive tuning. To overcome these issues, we introduce in this article PyDBS, a fully integrated and automated image processing workflow for DBS surgery.

Methods

   PyDBS consists of three image processing pipelines and three visualization modules assisting clinicians through the entire DBS surgical workflow, from the preoperative planning of electrode trajectories to the postoperative assessment of electrode placement. The system’s robustness, speed, and accuracy were assessed by means of a retrospective validation, based on 92 clinical cases.

Results

   The complete PyDBS workflow achieved satisfactory results in 92 % of tested cases, with a median processing time of 28 min per patient.

Conclusion

   The results obtained are compatible with the adoption of PyDBS in clinical practice.
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Metadaten
Titel
PyDBS: an automated image processing workflow for deep brain stimulation surgery
verfasst von
Tiziano D’Albis
Claire Haegelen
Caroline Essert
Sara Fernández-Vidal
Florent Lalys
Pierre Jannin
Publikationsdatum
01.02.2015
Verlag
Springer Berlin Heidelberg
Erschienen in
International Journal of Computer Assisted Radiology and Surgery / Ausgabe 2/2015
Print ISSN: 1861-6410
Elektronische ISSN: 1861-6429
DOI
https://doi.org/10.1007/s11548-014-1007-y

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