Keyword search (4,163 papers available)

"Int J Comput Assist Radiol Surg" Category Publications:

Title Authors PubMed ID
1 Automatic collateral circulation scoring in ischemic stroke using 4D CT angiography with low-rank and sparse matrix decomposition. Aktar M, Tampieri D, Rivaz H, Kersten-Oertel M, Xiao Y 32662055
ENCS
2 Two-stage ultrasound image segmentation using U-Net and test time augmentation. Amiri M; Brooks R; Behboodi B; Rivaz H; 32350786
IMAGING
3 MARIN: an open-source mobile augmented reality interactive neuronavigation system. Léger É; Reyes J; Drouin S; Popa T; Hall JA; Collins DL; Kersten-Oertel M; 32323206
PERFORM
4 Cognitive load associations when utilizing auditory display within image-guided neurosurgery. Plazak J, DiGiovanni DA, Collins DL, Kersten-Oertel M 30997635
ENCS
5 Deformable registration of preoperative MR, pre-resection ultrasound, and post-resection ultrasound images of neurosurgery. Rivaz H, Collins DL 25373447
PERFORM
6 Nonlinear deformation of tractography in ultrasound-guided low-grade gliomas resection. Xiao Y, Eikenes L, Reinertsen I, Rivaz H 29299739
PERFORM
7 Correction to: Nonlinear deformation of tractography in ultrasound-guided low-grade gliomas resection. Xiao Y, Eikenes L, Reinertsen I, Rivaz H 29392538
PERFORM
8 ARENA: Inter-modality affine registration using evolutionary strategy. Masoumi N, Xiao Y, Rivaz H 30535826
PERFORM

 

Title:MARIN: an open-source mobile augmented reality interactive neuronavigation system.
Authors:Léger É,  Reyes J,  Drouin S,  Popa T,  Hall JA,  Collins DL,  Kersten-Oertel M
Link:https://www.ncbi.nlm.nih.gov/pubmed/32323206
DOI:10.1007/s11548-020-02155-6
Publication:International journal of computer assisted radiology and surgery
Keywords:Augmented reality;  Image-guided intervention;  Interactive;  Mobile;  Neuronavigation; 
PMID:32323206 Category:Int J Comput Assist Radiol Surg Date Added:2020-04-24
Dept Affiliation: PERFORM
1 Department of Computer Science and Software Engineering, Concordia University, 1455 Boul. de Maisonneuve O., Montreal, QC H3G 1M8, Canada. etienne.leger@mail.concordia.ca.
2 Department of Computer Science and Software Engineering, Concordia University, 1455 Boul. de Maisonneuve O., Montreal, QC H3G 1M8, Canada.
3 Department of Software Engineering and Information Technology, École des Technologies Supérieures, 1100 Notre-Dame St. W., Montreal, QC H3G 1K3, Canada.
4 PERFORM Center, Concordia University, 1455 Boul. de Maisonneuve O., Montreal, QC H3G 1M8, Canada.
5 Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, 3801 University St., Montreal, QC H3A 2B4, Canada.
6 McConnell Brain Imaging Center at the Montreal Neurological Institute, McGill University, 3801 University

Description:

PURPOSE: Neuronavigation systems making use of augmented reality (AR) have been the focus of much research in the last couple of decades. In recent years, there has been considerable interest in using mobile devices for AR in the operating room (OR). We propose a complete system that performs real-time AR video augmentation on a mobile device in the context of image-guided neurosurgery.

METHODS: MARIN (mobile augmented reality interactive neuronavigation system) improves upon the state of the art in terms of performance, allowing real-time augmentation, and interactivity by allowing users to interact with the displayed data. The system was tested in a user study with 17 subjects for qualitative and quantitative evaluation in the context of target localization and brought into the OR for preliminary feasibility tests, where qualitative feedback from surgeons was obtained.

RESULTS: The results of the user study showed that MARIN performs significantly better in terms of both time ([Formula: see text]) and accuracy ([Formula: see text]) for the task of target localization in comparison with a traditional image-guided neurosurgery (IGNS) navigation system. Further, MARIN AR visualization was found to be more intuitive and allowed users to estimate target depth more easily.

CONCLUSION: MARIN improves upon previously proposed mobile AR neuronavigation systems with its real-time performance, higher accuracy, full integration in the normal workflow and greater interactivity and customizability of the displayed information. The improvement in efficiency and usability over previous systems will facilitate bringing AR into the OR.

PMID: 32323206 [PubMed - indexed for MEDLINE]




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