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Erschienen in: Journal of Digital Imaging 5/2015

01.10.2015

Assessment of DICOM Viewers Capable of Loading Patient-specific 3D Models Obtained by Different Segmentation Platforms in the Operating Room

verfasst von: Giuseppe Lo Presti, Marina Carbone, Damiano Ciriaci, Daniele Aramini, Mauro Ferrari, Vincenzo Ferrari

Erschienen in: Journal of Imaging Informatics in Medicine | Ausgabe 5/2015

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Abstract

Patient-specific 3D models obtained by the segmentation of volumetric diagnostic images play an increasingly important role in surgical planning. Surgeons use the virtual models reconstructed through segmentation to plan challenging surgeries. Many solutions exist for the different anatomical districts and surgical interventions. The possibility to bring the 3D virtual reconstructions with native radiological images in the operating room is essential for fostering the use of intraoperative planning. To the best of our knowledge, current DICOM viewers are not able to simultaneously connect to the picture archiving and communication system (PACS) and import 3D models generated by external platforms to allow a straight integration in the operating room. A total of 26 DICOM viewers were evaluated: 22 open source and four commercial. Two DICOM viewers can connect to PACS and import segmentations achieved by other applications: Synapse 3D® by Fujifilm and OsiriX by University of Geneva. We developed a software network that converts diffuse visual tool kit (VTK) format 3D model segmentations, obtained by any software platform, to a DICOM format that can be displayed using OsiriX or Synapse 3D. Both OsiriX and Synapse 3D were suitable for our purposes and had comparable performance. Although Synapse 3D loads native images and segmentations faster, the main benefits of OsiriX are its user-friendly loading of elaborated images and it being both free of charge and open source.
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Metadaten
Titel
Assessment of DICOM Viewers Capable of Loading Patient-specific 3D Models Obtained by Different Segmentation Platforms in the Operating Room
verfasst von
Giuseppe Lo Presti
Marina Carbone
Damiano Ciriaci
Daniele Aramini
Mauro Ferrari
Vincenzo Ferrari
Publikationsdatum
01.10.2015
Verlag
Springer US
Erschienen in
Journal of Imaging Informatics in Medicine / Ausgabe 5/2015
Print ISSN: 2948-2925
Elektronische ISSN: 2948-2933
DOI
https://doi.org/10.1007/s10278-015-9786-4

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