Keyword search (3,171 papers available)


Automatic collateral circulation scoring in ischemic stroke using 4D CT angiography with low-rank and sparse matrix decomposition.

Author(s): Aktar M, Tampieri D, Rivaz H, Kersten-Oertel M, Xiao Y

Int J Comput Assist Radiol Surg. 2020 Jul 14;: Authors: Aktar M, Tampieri D, Rivaz H, Kersten-Oertel M, Xiao Y

Article GUID: 32662055
Two-stage ultrasound image segmentation using U-Net and test time augmentation.

Author(s): Amiri M; Brooks R; Behboodi B; Rivaz H;

PURPOSE: Detecting breast lesions using ultrasound imaging is an important application of computer-aided diagnosis systems. Several automatic methods have been proposed for breast lesion detection and segmentation; however, due to the ultrasound artefacts, ...

Article GUID: 32350786
MARIN: an open-source mobile augmented reality interactive neuronavigation system.

Author(s): Léger É; Reyes J; Drouin S; Popa T; Hall JA; Collins DL; Kersten-Oertel M;

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 pro...

Article GUID: 32323206
Cognitive load associations when utilizing auditory display within image-guided neurosurgery.

Author(s): Plazak J, DiGiovanni DA, Collins DL, Kersten-Oertel M

Int J Comput Assist Radiol Surg. 2019 Apr 17;: Authors: Plazak J, DiGiovanni DA, Collins DL, Kersten-Oertel M

Article GUID: 30997635
Deformable registration of preoperative MR, pre-resection ultrasound, and post-resection ultrasound images of neurosurgery.

Author(s): Rivaz H, Collins DL

Int J Comput Assist Radiol Surg. 2015 Jul;10(7):1017-28 Authors: Rivaz H, Collins DL

Article GUID: 25373447
Nonlinear deformation of tractography in ultrasound-guided low-grade gliomas resection.

Author(s): Xiao Y, Eikenes L, Reinertsen I, Rivaz H

Int J Comput Assist Radiol Surg. 2018 Mar;13(3):457-467 Authors: Xiao Y, Eikenes L, Reinertsen I, Rivaz H

Article GUID: 29299739
Correction to: Nonlinear deformation of tractography in ultrasound-guided low-grade gliomas resection.

Author(s): Xiao Y, Eikenes L, Reinertsen I, Rivaz H

Int J Comput Assist Radiol Surg. 2018 03;13(3):469 Authors: Xiao Y, Eikenes L, Reinertsen I, Rivaz H

Article GUID: 29392538
ARENA: Inter-modality affine registration using evolutionary strategy.

Author(s): Masoumi N, Xiao Y, Rivaz H

Int J Comput Assist Radiol Surg. 2019 Mar;14(3):441-450 Authors: Masoumi N, Xiao Y, Rivaz H

Article GUID: 30535826
Title:Deformable registration of preoperative MR, pre-resection ultrasound, and post-resection ultrasound images of neurosurgery.
Authors:Rivaz H,  Collins DL
Link:https://www.ncbi.nlm.nih.gov/pubmed/25373447?dopt=Abstract
Category:Int J Comput Assist Radiol Surg
PMID:25373447
Dept Affiliation: PERFORM
1 PERFORM Centre, Department of Electrical and Computer Engineering, Concordia University, 1455 Maisonneuve West, Montreal, QC, H3G 1M8, Canada, hrivaz@ece.concordia.ca.

Description:

Deformable registration of preoperative MR, pre-resection ultrasound, and post-resection ultrasound images of neurosurgery.

Int J Comput Assist Radiol Surg. 2015 Jul;10(7):1017-28

Authors: Rivaz H, Collins DL

Abstract

PURPOSE: Sites that use ultrasound (US) in image-guided neurosurgery (IGNS) of brain tumors generally have three sets of imaging data: preoperative magnetic resonance (MR) image, pre-resection US, and post-resection US. The MR image is usually acquired days before the surgery, the pre-resection US is obtained after the craniotomy but before the resection, and finally, the post-resection US scan is performed after the resection of the tumor. The craniotomy and tumor resection both cause brain deformation, which significantly reduces the accuracy of the MR-US alignment.

METHOD: Three unknown transformations exist between the three sets of imaging data: MR to pre-resection US, pre- to post-resection US, and MR to post-resection US. We use two algorithms that we have recently developed to perform the first two registrations (i.e., MR to pre-resection US and pre- to post-resection US). Regarding the third registration (MR to post-resection US), we evaluate three strategies. The first method performs a registration between the MR and pre-resection US, and another registration between the pre- and post-resection US. It then composes the two transformations to register MR and post-resection US; we call this method compositional registration. The second method ignores the pre-resection US and directly registers the MR and post-resection US; we refer to this method as direct registration. The third method is a combination of the first and second: it uses the solution of the compositional registration as an initial solution for the direct registration method. We call this method group-wise registration.

RESULTS: We use data from 13 patients provided in the MNI BITE database for all of our analysis. Registration of MR and pre-resection US reduces the average of the mean target registration error (mTRE) from 4.1 to 2.4 mm. Registration of pre- and post-resection US reduces the average mTRE from 3.7 to 1.5 mm. Regarding the registration of MR and post-resection US, all three strategies reduce the mTRE. The initial average mTRE is 5.9 mm, which reduces to 3.3 mm with the compositional method, 2.9 mm with the direct technique, and 2.8 mm with the group-wise method.

CONCLUSION: Deformable registration of MR and pre- and post-resection US images significantly improves their alignment. Among the three methods proposed for registering the MR to post-resection US, the group-wise method gives the lowest TRE values. Since the running time of all registration algorithms is less than 2 min on one core of a CPU, they can be integrated into IGNS systems for interactive use during surgery.

PMID: 25373447 [PubMed - indexed for MEDLINE]