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  • 1
    Keywords: SURGERY ; REGISTRATION ; TIME-OF-FLIGHT ; toolkit ; image-guided therapy ; Intra-operative surface acquisition ; open-source software ; Range data
    Abstract: PURPOSE: The time-of-flight (ToF) technique is an emerging technique for rapidly acquiring distance information and is becoming increasingly popular for intra-operative surface acquisition. Using the ToF technique as an intra-operative imaging modality requires seamless integration into the clinical workflow. We thus aim to integrate ToF support in an existing framework for medical image processing. METHODS: MITK-ToF was implemented as an extension of the open-source C++ Medical Imaging Interaction Toolkit (MITK) and provides the basic functionality needed for rapid prototyping and development of image-guided therapy (IGT) applications that utilize range data for intra-operative surface acquisition. This framework was designed with a module-based architecture separating the hardware-dependent image acquisition task from the processing of the range data. RESULTS: The first version of MITK-ToF has been released as an open-source toolkit and supports several ToF cameras and basic processing algorithms. The toolkit, a sample application, and a tutorial are available from http://mitk.org . CONCLUSIONS: With the increased popularity of time-of-flight cameras for intra-operative surface acquisition, integration of range data supports into medical image processing toolkits such as MITK is a necessary step. Handling acquisition of range data from different cameras and processing of the data requires the establishment and use of software design principles that emphasize flexibility, extendibility, robustness, performance, and portability. The open-source toolkit MITK-ToF satisfies these requirements for the image-guided therapy community and was already used in several research projects.
    Type of Publication: Journal article published
    PubMed ID: 21626396
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  • 2
    Keywords: SURGERY ; REGISTRATION ; LIGHT ; SENSORS ; INTEGRATED BUNDLE ADJUSTMENT ; GEOMETRIC SELF-CALIBRATION ; RANGE CAMERA ; TOF CAMERAS
    Abstract: Purpose: In image-guided surgery (IGS) intraoperative image acquisition of tissue shape, motion, and morphology is one of the main challenges. Recently, time-of-flight (ToF) cameras have emerged as a new means for fast range image acquisition that can be used for multimodal registration of the patient anatomy during surgery. The major drawbacks of ToF cameras are systematic errors in the image acquisition technique that compromise the quality of the measured range images. In this paper, we propose a calibration concept that, for the first time, accounts for all known systematic errors affecting the quality of ToF range images. Laboratory and in vitro experiments assess its performance in the context of IGS.Methods: For calibration the camera-related error sources depending on the sensor, the sensor temperature and the set integration time are corrected first, followed by the scene-specific errors, which are modeled as function of the measured distance, the amplitude and the radial distance to the principal point of the camera. Accounting for the high accuracy demands in IGS, we use a custom-made calibration device to provide reference distance data, the cameras are calibrated too. To evaluate the mitigation of the error, the remaining residual error after ToF depth calibration was compared with that arising from using the manufacturer routines for several state-of-the-art ToF cameras. The accuracy of reconstructed ToF surfaces was investigated after multimodal registration with computed tomography (CT) data of liver models by assessment of the target registration error (TRE) of markers introduced in the livers.Results: For the inspected distance range of up to 2 m, our calibration approach yielded a mean residual error to reference data ranging from 1.5 +/- 4.3 mm for the best camera to 7.2 +/- 11.0 mm. When compared to the data obtained from the manufacturer routines, the residual error was reduced by at least 78% from worst calibration result to most accurate manufacturer data. After registration of the CT data with the ToF data, the mean TRE ranged from 3.7 +/- 2.1 mm for point-based and 5.7 +/- 1.9 mm for surface-based registration for the best camera to 6.2 +/- 3.4 and 11.1 +/- 2.8 mm, respectively. Compared to data provided by the manufacturer, the mean TRE decreased by 8%-60% for point-based and by 18%-74% for surface-based registration.Conclusions: Using the proposed calibration approach improved the measurement accuracy of all investigated ToF cameras. Although evaluated in the context of intraoperative image acquisition, the proposed calibration procedure can easily be applied to other medical applications using ToF cameras, such as patient positioning or respiratory motion tracking in radiotherapy.
    Type of Publication: Journal article published
    PubMed ID: 23927355
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  • 3
    Keywords: IN-VITRO ; tumor ; Germany ; human ; MODEL ; THERAPY ; VITRO ; CT ; SYSTEM ; liver ; ACCURACY ; computed tomography ; SURGERY ; TARGET ; REGISTRATION ; STRATEGIES ; COMPUTED-TOMOGRAPHY ; MOTION ; TRACKING ; BIOPSY ; RE ; THERAPIES ; ABLATION ; THIN-PLATE SPLINES ; RESPIRATORY MOTION ; ENGLAND ; THERMAL ABLATION ; navigation ; respiratory liver motion simulator ; POSITION ; INTERVENTIONS ; NEEDLES ; DEVICE ; deformation model ; image-guided systems ; interventional radiology ; needle insertion ; respiratory motion compensation
    Abstract: Computed tomography (CT) guided minimally invasive procedures in the liver, such as tumor biopsy and thermal ablation therapy, require precise targeting of hepatic structures that are subject to breathing motion. To facilitate needle placement, we introduced a navigation system which uses needle-shaped optically tracked navigation aids and a real-time deformation model to continuously estimate the position of a moving target. In this study, we assessed the target position estimation accuracy of our system in vitro with a custom-designed respiratory liver motion simulator. Several real-time compatible transformations were compared as a basis for the deformation model and were evaluated in a set of experiments using different arrangements of three navigation aids in two porcine and two human livers. Furthermore, we investigated different placement strategies for the case where only two needles are used for motion compensation. Depending on the transformation and the placement of the navigation aids, our system yielded a root mean square (RMS) target position estimation error in the range of 0.7 mm to 2.9 mm throughout the breathing cycle generated by the motion simulator. Affine transformations and spline transformations performed comparably well (overall RMS 〈 2 mm) and were considerably better than rigid transformations. When two navigation aids were used for motion compensation instead of three, a diagonal arrangement of the needles yielded the best results. This study suggests that our navigation system could significantly improve the clinical treatment standard for CT-guided interventions in the liver
    Type of Publication: Journal article published
    PubMed ID: 18432412
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