Keyword search (4,163 papers available)

"registration" Keyword-tagged Publications:

Title Authors PubMed ID
1 Statistical shape model-based estimation of registration error in computer-assisted total knee arthroplasty Gheflati B; Mirzaei M; Zuhars J; Rottoo S; Rivaz H; 41495592
ENCS
2 A database of magnetic resonance imaging-transcranial ultrasound co-registration Alizadeh M; Collins DL; Kersten-Oertel M; Xiao Y; 39920905
SOH
3 Data-Weighted Multivariate Generalized Gaussian Mixture Model: Application to Point Cloud Robust Registration Ge B; Najar F; Bouguila N; 37754943
ENCS
4 Robust landmark-based brain shift correction with a Siamese neural network in ultrasound-guided brain tumor resection Pirhadi A; Salari S; Ahmad MO; Rivaz H; Xiao Y; 36306056
PERFORM
5 DiffeoRaptor: diffeomorphic inter-modal image registration using RaPTOR Masoumi N; Rivaz H; Ahmad MO; Xiao Y; 36173541
ENCS
6 Multimodal 3D ultrasound and CT in image-guided spinal surgery: public database and new registration algorithms Masoumi N; Belasso CJ; Ahmad MO; Benali H; Xiao Y; Rivaz H; 33683544
PERFORM
7 REtroSpective Evaluation of Cerebral Tumors (RESECT): A clinical database of pre-operative MRI and intra-operative ultrasound in low-grade glioma surgeries. Xiao Y, Fortin M, Unsgård G, Rivaz H, Reinertsen I 28391601
PERFORM
8 A dataset of multi-contrast population-averaged brain MRI atlases of a Parkinson׳s disease cohort. Xiao Y, Fonov V, Chakravarty MM, Beriault S, Al Subaie F, Sadikot A, Pike GB, Bertrand G, Collins DL 28491942
PERFORM
9 Nonlinear deformation of tractography in ultrasound-guided low-grade gliomas resection. Xiao Y, Eikenes L, Reinertsen I, Rivaz H 29299739
PERFORM
10 Combining intraoperative ultrasound brain shift correction and augmented reality visualizations: a pilot study of eight cases. Gerard IJ, Kersten-Oertel M, Drouin S, Hall JA, Petrecca K, De Nigris D, Di Giovanni DA, Arbel T, Collins DL 29392162
PERFORM
11 ARENA: Inter-modality affine registration using evolutionary strategy. Masoumi N, Xiao Y, Rivaz H 30535826
PERFORM
12 Gesture-based registration correction using a mobile augmented reality image-guided neurosurgery system. Léger É, Reyes J, Drouin S, Collins DL, Popa T, Kersten-Oertel M 30800320
PERFORM

 

Title:Combining intraoperative ultrasound brain shift correction and augmented reality visualizations: a pilot study of eight cases.
Authors:Gerard IJKersten-Oertel MDrouin SHall JAPetrecca KDe Nigris DDi Giovanni DAArbel TCollins DL
Link:https://www.ncbi.nlm.nih.gov/pubmed/29392162?dopt=Abstract
DOI:10.1117/1.JMI.5.2.021210
Publication:Journal of medical imaging (Bellingham, Wash.)
Keywords:augmented realitybrain shiftbrain tumorimage-guided neurosurgeryregistration
PMID:29392162 Category:J Med Imaging (Bellingham) Date Added:2019-04-15
Dept Affiliation: PERFORM
1 McGill University, Montreal Neurological Institute and Hospital, Department of Biomedical Engineering, Montreal, Québec, Canada.
2 Concordia University, PERFORM Centre, Department of Computer Science and Software Engineering, Montreal, Québec, Canada.
3 McGill University, Montreal Neurological Institute and Hospital, Department of Neurology and Neurosurgery, Montreal, Québec, Canada.
4 McGill University, Centre for Intelligent Machines, Department of Electrical and Computer Engineering, Montreal, Québec, Canada.

Description:

Combining intraoperative ultrasound brain shift correction and augmented reality visualizations: a pilot study of eight cases.

J Med Imaging (Bellingham). 2018 Apr;5(2):021210

Authors: Gerard IJ, Kersten-Oertel M, Drouin S, Hall JA, Petrecca K, De Nigris D, Di Giovanni DA, Arbel T, Collins DL

Abstract

We present our work investigating the feasibility of combining intraoperative ultrasound for brain shift correction and augmented reality (AR) visualization for intraoperative interpretation of patient-specific models in image-guided neurosurgery (IGNS) of brain tumors. We combine two imaging technologies for image-guided brain tumor neurosurgery. Throughout surgical interventions, AR was used to assess different surgical strategies using three-dimensional (3-D) patient-specific models of the patient's cortex, vasculature, and lesion. Ultrasound imaging was acquired intraoperatively, and preoperative images and models were registered to the intraoperative data. The quality and reliability of the AR views were evaluated with both qualitative and quantitative metrics. A pilot study of eight patients demonstrates the feasible combination of these two technologies and their complementary features. In each case, the AR visualizations enabled the surgeon to accurately visualize the anatomy and pathology of interest for an extended period of the intervention. Inaccuracies associated with misregistration, brain shift, and AR were improved in all cases. These results demonstrate the potential of combining ultrasound-based registration with AR to become a useful tool for neurosurgeons to improve intraoperative patient-specific planning by improving the understanding of complex 3-D medical imaging data and prolonging the reliable use of IGNS.

PMID: 29392162 [PubMed]





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