Augmenting Intraoperative 3D Ultrasound with Preoperative Models for Navigation in Liver Surgery

Lange, Thomas; Eulenstein, Sebastian; Hünerbein, M.; Lamecker, Hans; Schlag, P.M.

doi:10.1007/978-3-540-30136-3_66

Cited by 60 publications

(50 citation statements)

References 20 publications

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“…Therefore, our method effectively reduces the number of incorrect pairings without limiting the capture range of the registration algorithm. While our algorithm shares some similarities with the procedure described by Lange et al (2004), there are some important differences. Our procedure is applied to interventional brain imaging, while Lange's technique was applied to liver.…”

Section: Vessel Based Registrationmentioning

confidence: 99%

Validation of vessel-based registration for correction of brain shift

Reinertsen

Descoteaux

Siddiqi

et al. 2007

Medical Image Analysis

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The displacement and deformation of brain tissue is a major source of error in image-guided neurosurgery systems. We have designed and implemented a method to detect and correct brain shift using pre-operative MR images and intraoperative Doppler ultrasound data and present its validation with both real and simulated data. The algorithm uses segmented vessels from both modalities, and estimates the deformation using a modified version of the iterative closest point (ICP) algorithm. We use the least trimmed squares (LTS) to reduce the number of outliers in the point matching procedure. These points are used to drive a thin-plate spline transform to achieve non-linear registration. Validation was completed in two parts. First, the technique was tested and validated using realistic simulations where the results were compared to the known deformation. The registration technique recovered 75% of the deformation in the region of interest accounting for deformations as large as 20 mm. Second, we performed a PVA-cryogel phantom study where both MR and ultrasound images of the phantom were obtained for three different deformations. The registration results based on MR data were used as a gold standard to evaluate the performance of the ultrasound based registration. On average, deformations of 7.5 mm magnitude were corrected to within 1.6 mm for the ultrasound based registration and 1.07 mm for the MR based registration.

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Section: Vessel Based Registrationmentioning

confidence: 99%

Validation of vessel-based registration for correction of brain shift

Reinertsen

Descoteaux

Siddiqi

et al. 2007

Medical Image Analysis

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“…The use of color Doppler ultrasound aids the automatic feature extraction of vessel structures, which can in turn be used for feature-based registration [14]- [16]. In [14], liver vessel features are extracted from both preoperative MRI/CT data and intraoperative 3-D power-Doppler ultrasound data.…”

confidence: 99%

“…In [14], liver vessel features are extracted from both preoperative MRI/CT data and intraoperative 3-D power-Doppler ultrasound data. The registration is initiated with a few manually selected landmarks, and a rigid transformation is then estimated using a modified ICP method, which takes the vessel topology into account.…”

confidence: 99%

Integrating Diagnostic B-Mode Ultrasonography Into CT-Based Radiation Treatment Planning

Wein

Röper²,

Navab³

2007

IEEE Trans. Med. Imaging

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Abstract-This paper presents methods and a clinical procedure for integrating B-mode ultrasound images tagged with position information with a planning computed tomography (CT) scan for radiotherapy. A workflow is described that allows the integration of these modalities into the clinic. A surface mapping approach provides a preregistration of the ultrasound image borders onto the patient's skin. Successively, a set of individual ultrasound images from a freehand sweep is chosen by the physician. These images are automatically registered with the planning CT scan using novel intensity-based methods. We put a particular focus on deriving an appropriate similarity measure based on the physical properties and artifacts of ultrasound. A combination of a weighted mutual information term, edge correlation, clamping to the skin surface, and occlusion detection is able to assess the alignment of structures in ultrasound images and information reconstructed from the CT data. We demonstrate the practicality of our methods on five patients with head and neck tumors and cervical lymph node metastases and provide a detailed report on the conducted experiments, including the setup, calibration, acquisition, and verification of our algorithms. The mean target registration error on nine data sets is 3.9 mm. Thus, the additional information about intranodal architecture and fulfillment of malignancy criteria derived from a high-resolution ultrasonography of lymph nodes can be localized and visualized in the CT scan coordinate space and is made available for further radiation treatment planning.

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“…Few automatic ultrasound-magnetic resonance imaging (MRI) registration methods have been described in the literature. Lange et al 5 developed a fast nonrigid registration method based on vessel centerlines as a technique for mapping preoperative models into intraoperative 3D ultrasound. Their registration process made use of a combination of the Iterative Closest Point (ICP) algorithm and multilevel B-Splines and required minimal user interaction (a first step consisting of coarse rigid alignment of the vessels centerlines required 3 to 4 manually given paired landmarks).…”

Section: Introductionmentioning

confidence: 99%

Visualization of hepatic arteries with 3D ultrasound during intra-arterial therapies

Gérard

Tang

Badoual

et al. 2016

Medical Imaging 2016: Image-Guided Procedures, Robotic Interventions, and Modeling

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Liver cancer represents the second most common cause of cancer-related mortality worldwide. The prognosis is poor with an overall mortality of 95%. Moreover, most hepatic tumors are unresectable due to their advanced stage at discovery or poor underlying liver function. Tumor embolization by intra-arterial approaches is the current standard of care for advanced cases of hepatocellular carcinoma. These therapies rely on the fact that the blood supply of primary hepatic tumors is predominantly arterial. Feedback on blood flow velocities in the hepatic arteries is crucial to ensure maximal treatment efficacy on the targeted masses. Based on these velocities, the intra-arterial injection rate is modulated for optimal infusion of the chemotherapeutic drugs into the tumorous tissue. While Doppler ultrasound is a welldocumented technique for the assessment of blood flow, 3D visualization of vascular anatomy with ultrasound remains challenging. In this paper we present an image-guidance pipeline that enables the localization of the hepatic arterial branches within a 3D ultrasound image of the liver. A diagnostic Magnetic resonance angiography (MRA) is first processed to automatically segment the hepatic arteries. A non-rigid registration method is then applied on the portal phase of the MRA volume with a 3D ultrasound to enable the visualization of the 3D mesh of the hepatic arteries in the Doppler images. To evaluate the performance of the proposed workflow, we present initial results from porcine models and patient images.

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Augmenting Intraoperative 3D Ultrasound with Preoperative Models for Navigation in Liver Surgery

Cited by 60 publications

References 20 publications

Validation of vessel-based registration for correction of brain shift

Validation of vessel-based registration for correction of brain shift

Integrating Diagnostic B-Mode Ultrasonography Into CT-Based Radiation Treatment Planning

Visualization of hepatic arteries with 3D ultrasound during intra-arterial therapies

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