An integrated visualization system for surgical planning and guidance using image fusion and an open MR

By D. Gering, A. Nabavi, Ron Kikinis, N. Hata, Lauren J. O'Donnell, W. Grimson, F. Jolesz, P. Black, William M. Wells. Journal of Magnetic Resonance Imaging, 2001

398 citations recorded by the source corpus.

Subfields: Computational Mechanics, Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/84ff181750f57f25237e50704b186b22450d1ddf

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Mechanics

In Computer Graphics and Computer-Aided Design

In Computer Vision and Pattern Recognition

Citations in the corpus

Design and validation of Segment - freely available software for cardiovascular image analysis (2010, background): “Yet another well-known application is Slicer http://www.slicer.org/ [30].”
3D Slicer as an Image Computing Platform for the Quantitative Imaging Network (2012, background): “Initially envisioned as a neurosurgical guidance, visualization and analysis system [7,9], over the last decade, Slicer has evolved into an integrated platform that has been applied in a variety of clinical and preclinical research applications, as well as for the analysis of nonmedical images [10–2”
Medical image registration: a review (2014, methodology): “…single-photon emission computed tomography (SPECT) or functional magnetic resonance imaging; intervention and treatment planning (Gering et al. 1999; Gering et al. 2001; Staring et al. 2009); computer-aided diagnosis and disease following-up (Huang et al. 2009); surgery simulation (Miller et al.…”
OpenIGTLink: an open network protocol for image-guided therapy environment (2009, methodology): “To utilize various types of tracking devices, including encoded mechanical arms, optical tracking systems and electromagnetic tracking (28) from surgical navigation software in image-guided therapy, we implemented a client–server architecture for tracking devices and navigation software integration,”
User-guided 3D active contour segmentation of anatomical structures: Significantly improved efficiency and reliability (2006, methodology): “For instance, large-scale packages such as Mayo Analyze (Robb and Hanson, 1995) and the open-source 3D Slicer (Gering et al., 2001) include 3D active contour segmentation modules, and the NIH MIPAV tool (McAuliffe et al.”
A Generative Model for Image Segmentation Based on Label Fusion (2010, neutral): “Such supervised segmentation tools are commonly used in many medical imaging applications, including surgical planning [27] and the study of disease progression, aging or healthy development [23], [50], [74].”
Survey of Non-Rigid Registration Tools in Medicine (2017, background): “In the medical field, image registration is a key component in several areas including the fusion of morphologic and functional images [1]; image subtraction [2]; intervention planning [3]; computeraided diagnosis (CAD) and treatment follow-up [4]; intervention simulations [5]; atlas building [6–8];”
DRAMMS: Deformable Registration via Attribute Matching and Mutual-Saliency Weighting (2009, background): “and Apostolova, 2007) and image-guided surgery (e.g., Muratore et al., 2003; Gering et al., 2001; Hata et al., 1998).”