Automatic CT-ultrasound registration for diagnostic imaging and image-guided intervention

By Wolfgang Wein, S. Brunke, Ali Kamen, M. Callstrom, Nassir Navab. Medical Image Anal., 2008

401 citations recorded by the source corpus.

The fusion of tracked ultrasound with CT has benefits for a variety of clinical applications, however extensive manual effort is usually required for correct registration. We developed new methods that allow one to simulate medical ultrasound from CT in real-time, reproducing the majority of ultrasonic imaging effects. They are combined with a robust similarity measure that assesses the correlation of a combination of signals extracted from CT with ultrasound, without knowing the influence of each signal. This serves as the foundation of a fully automatic registration, that aligns a 3D ultrasound sweep with the corresponding tomographic modality using a rigid or an affine transformation model, without any manual interaction. These techniques were evaluated in a study involving 25 patients with indeterminate lesions in liver and kidney. The clinical setup, acquisition and registration workflow is described, along with the evaluation of the registration accuracy with respect to physician-defined Ground Truth. Our new algorithm correctly registers without any manual interaction in 76% of the cases, the average RMS TRE over multiple target lesions throughout the liver is 8.1mm.

Subfields: Pulmonary and Respiratory Medicine, Radiation, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/8fea7450a0b2fa33b39d35a9649109b1dd39aaf6

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In Pulmonary and Respiratory Medicine

In Radiation

In Radiology, Nuclear Medicine and Imaging

Citations in the corpus

Slice-to-volume medical image registration: a survey (2017, methodology): “Note that, as described in the next section, several papers that propose sensor based methods, are actually a combination of this technology with some image-based registration technique, resulting in what we call a hybrid method.”
Deformable Medical Image Registration: A Survey (2013, background): “Wein et al. [364] simulated an US image in order to tackle the problem of CT-to-US rigid/afﬁne registration.”
A review of 3D/2D registration methods for image-guided interventions (2012, background): “…CT, MR, or US image (Jaffray et al., 2002; Pouliot et al., 2005; Jolesz, 2005; Penney et al., 2006) and 3D/2D volume-to-slice (Comeau et al., 2000; Wein et al., 2008; Micu et al., 2006; Birkfellner et al., 2007; Frühwald et al., 2009; Hummel et al., 2008; Fei et al., 2003) and (endoscopic)…”
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];”