Real-time organ motion tracking and fast image registration system for MRI-guided surgery

2005 ◽  
Vol 37 (1) ◽  
pp. 83-92 ◽  
Author(s):  
Junichi Tokuda ◽  
Masaya Hirano ◽  
Tetsuji Tsukamoto ◽  
Takeyoshi Dohi ◽  
Nobuhiko Hata
Keyword(s):  
Image Registration ◽  
Real Time ◽  
Motion Tracking ◽  
Organ Motion ◽  
Registration System ◽  
Guided Surgery ◽  
Mri Guided

A Hybrid Image Registration and Matching Framework for Real-Time Motion Tracking in MRI-Guided Radiotherapy

2018 ◽  
Vol 65 (1) ◽  
pp. 131-139 ◽  
Author(s):  
Matteo Seregni ◽  
Chiara Paganelli ◽  
Paul Summers ◽  
Massimo Bellomi ◽  
Guido Baroni ◽  
...  
Keyword(s):  
Image Registration ◽  
Real Time ◽  
Motion Tracking ◽  
Time Motion ◽  
Mri Guided

scholarly journals Frameless neuronavigation with computer vision and real-time tracking for bedside external ventricular drain placement: a cadaveric study

2021 ◽  
pp. 1-10
Author(s):  
Faith C. Robertson ◽  
Raahil M. Sha ◽  
Jose M. Amich ◽  
Walid Ibn Essayed ◽  
Avinash Lal ◽  
...  
Keyword(s):  
Computer Vision ◽  
Image Registration ◽  
Real Time ◽  
Tracking System ◽  
External Ventricular Drain ◽  
Surface Registration ◽  
Ct Scans ◽  
Registration System ◽  
Registration Error ◽  
Real Time Tracking

OBJECTIVE A major obstacle to improving bedside neurosurgical procedure safety and accuracy with image guidance technologies is the lack of a rapidly deployable, real-time registration and tracking system for a moving patient. This deficiency explains the persistence of freehand placement of external ventricular drains, which has an inherent risk of inaccurate positioning, multiple passes, tract hemorrhage, and injury to adjacent brain parenchyma. Here, the authors introduce and validate a novel image registration and real-time tracking system for frameless stereotactic neuronavigation and catheter placement in the nonimmobilized patient. METHODS Computer vision technology was used to develop an algorithm that performed near-continuous, automatic, and marker-less image registration. The program fuses a subject’s preprocedure CT scans to live 3D camera images (Snap-Surface), and patient movement is incorporated by artificial intelligence–driven recalibration (Real-Track). The surface registration error (SRE) and target registration error (TRE) were calculated for 5 cadaveric heads that underwent serial movements (fast and slow velocity roll, pitch, and yaw motions) and several test conditions, such as surgical draping with limited anatomical exposure and differential subject lighting. Six catheters were placed in each cadaveric head (30 total placements) with a simulated sterile technique. Postprocedure CT scans allowed comparison of planned and actual catheter positions for user error calculation. RESULTS Registration was successful for all 5 cadaveric specimens, with an overall mean (± standard deviation) SRE of 0.429 ± 0.108 mm for the catheter placements. Accuracy of TRE was maintained under 1.2 mm throughout specimen movements of low and high velocities of roll, pitch, and yaw, with the slowest recalibration time of 0.23 seconds. There were no statistically significant differences in SRE when the specimens were draped or fully undraped (p = 0.336). Performing registration in a bright versus a dimly lit environment had no statistically significant effect on SRE (p = 0.742 and 0.859, respectively). For the catheter placements, mean TRE was 0.862 ± 0.322 mm and mean user error (difference between target and actual catheter tip) was 1.674 ± 1.195 mm. CONCLUSIONS This computer vision–based registration system provided real-time tracking of cadaveric heads with a recalibration time of less than one-quarter of a second with submillimetric accuracy and enabled catheter placements with millimetric accuracy. Using this approach to guide bedside ventriculostomy could reduce complications, improve safety, and be extrapolated to other frameless stereotactic applications in awake, nonimmobilized patients.

scholarly journals Validation of Fast Organ Tracking and Image Registration for MRI-Guided Surgery

2004 ◽  
Vol 16 (Supplement) ◽  
pp. 231-232
Author(s):  
Junichi Tokuda ◽  
Takeyoshi Dohi ◽  
Nobuhiko Hata ◽  
Masaya Hirano ◽  
Tetsuji Tsukamoto
Keyword(s):  
Image Registration ◽  
Guided Surgery ◽  
Mri Guided

Comparative study of NOTES alone vs. NOTES guided by a new image registration system for navigation in the mediastinum: A study in a porcine model

Endoscopy ◽  
2012 ◽  
Vol 44 (10) ◽  
Author(s):  
H Córdova ◽  
R San José Estépar ◽  
A Rodríguez-D'Jesús ◽  
G Martínez-Pallí ◽  
P Arguis ◽  
...  
Keyword(s):  
Image Registration ◽  
Comparative Study ◽  
Porcine Model ◽  
Registration System

Real-time motion tracking in image-guided oral implantology

2008 ◽  
Vol 4 (4) ◽  
pp. 339-347 ◽  
Author(s):  
Xiaojun Chen ◽  
Yanping Lin ◽  
Yiqun Wu ◽  
Chengtao Wang
Keyword(s):  
Real Time ◽  
Motion Tracking ◽  
Image Guided ◽  
Time Motion ◽  
Oral Implantology
Sign in / Sign up

Export Citation Format

Share Document