Accurate 3D-reconstruction and -navigation for high-precision minimal-invasive interventions

The current lateral skull base surgery is largely invasive since it requires wide exposure and direct visualization of anatomical landmarks to avoid damaging critical structures. A multi-port approach aiming to reduce such invasiveness has been recently investigated. Thereby three canals are drilled from the skull surface to the surgical region of interest: the first canal for the instrument, the second for the endoscope, and the third for material removal or an additional instrument. The transition to minimal invasive approaches in the lateral skull base surgery requires sub-millimeter accuracy and high outcome predictability, which results in high requirements for the image acquisition as well as for the navigation. Computed tomography (CT) is a non-invasive imaging technique allowing the visualization of the internal patient organs. Planning optimal drill channels based on patient-specific models requires high-accurate three-dimensional (3D) CT images. This thesis focuses on the reconstruction of high quality CT volumes. Therefore, two conventional imaging systems are investigated: spiral CT scanners and C-arm cone-beam CT (CBCT) systems. Spiral CT scanners acquire volumes with typically anisotropic resolution, i.e. the voxel spacing in the slice-selection-direction is larger than the in-the-plane spacing. A new super-resolution reconstruction approach is proposed to recover images with high isotropic resolution from two orthogonal low-resolution CT volumes. C-arm CBCT systems offers CT-like 3D imaging capabilities while being appropriate for interventional suites. A main drawback of these systems is the commonly encountered CT artifacts due to several limitations in the imaging system, such as the mechanical inaccuracies. This thesis contributes new methods to enhance the CBCT reconstruction quality by addressing two main reconstruction artifacts: the misalignment artifacts caused by mechanical inaccuracies, and the metal-artifacts caused by the presence of metal objects in the scanned region. CBCT scanners are appropriate for intra-operative image-guided navigation. For instance, they can be used to control the drill process based on intra-operatively acquired 2D fluoroscopic images. For a successful navigation, accurate estimate of C-arm pose relative to the patient anatomy and the associated surgical plan is required. A new algorithm has been developed to fulfill this task with high-precision. The performance of the introduced methods is demonstrated on simulated and real data

Accurate 3D-reconstruction and -navigation for high-precision minimal-invasive interventions

The current lateral skull base surgery is largely invasive since it requires wide exposure and direct visualization of anatomical landmarks to avoid damaging critical structures. A multi-port approach aiming to reduce such invasiveness has been recently investigated. Thereby three canals are drilled from the skull surface to the surgical region of interest: the first canal for the instrument, the second for the endoscope, and the third for material removal or an additional instrument. The transition to minimal invasive approaches in the lateral skull base surgery requires sub-millimeter accuracy and high outcome predictability, which results in high requirements for the image acquisition as well as for the navigation. Computed tomography (CT) is a non-invasive imaging technique allowing the visualization of the internal patient organs. Planning optimal drill channels based on patient-specific models requires high-accurate three-dimensional (3D) CT images. This thesis focuses on the reconstruction of high quality CT volumes. Therefore, two conventional imaging systems are investigated: spiral CT scanners and C-arm cone-beam CT (CBCT) systems. Spiral CT scanners acquire volumes with typically anisotropic resolution, i.e. the voxel spacing in the slice-selection-direction is larger than the in-the-plane spacing. A new super-resolution reconstruction approach is proposed to recover images with high isotropic resolution from two orthogonal low-resolution CT volumes. C-arm CBCT systems offers CT-like 3D imaging capabilities while being appropriate for interventional suites. A main drawback of these systems is the commonly encountered CT artifacts due to several limitations in the imaging system, such as the mechanical inaccuracies. This thesis contributes new methods to enhance the CBCT reconstruction quality by addressing two main reconstruction artifacts: the misalignment artifacts caused by mechanical inaccuracies, and the metal-artifacts caused by the presence of metal objects in the scanned region. CBCT scanners are appropriate for intra-operative image-guided navigation. For instance, they can be used to control the drill process based on intra-operatively acquired 2D fluoroscopic images. For a successful navigation, accurate estimate of C-arm pose relative to the patient anatomy and the associated surgical plan is required. A new algorithm has been developed to fulfill this task with high-precision. The performance of the introduced methods is demonstrated on simulated and real data

On-the-Fly Geometrical Calibration Fine-Tuning of a Mobile C-Arm CBCT System : Geometrische Online-Nachoptimierung der Kalibrierung eines mobilen CBCT-C-Bogens

C-arm cone-beam computed tomography (CBCT) offers CT-like 3D imaging capabilities while being appropriate for interventional suites. 3D images are reconstructed based on 2D projections gathered during the rotation of the C-arm around the object under investigation. It is mandatory to provide accurate geometrical projection parameters for each acquired 2D image, otherwise significant CT artifacts may be induced in the reconstructed 3D volume. Usually, a pre-calibration (offline calibration) using an X-ray phantom is preformed under the assumption that the C-arm motion is reproducible. Thereby, stochastic misalignments due to the open design of mobile C-arm CBCT systems are not considered. In this article we introduce a novel online calibration algorithm to compensate stochastic mechanical inaccuracies. The performance of the proposed method is demonstrated on simulated and real data. Intraoperative 3D-Röntgenbildgebung ist zum Standard in der modernen Chirurgie geworden. Mithilfe von mobilen C-Bögen können 3D Computertomographie-ähnliche Bilder intraoperativ aufgenommen werden. Während der Rotation des C-Bogens um den Patienten werden 2D-Projektionen akquiriert, die zur Rekonstruktion der Volumendaten verwendet werden. Präzise geometrische Projektionsparameter (Position der Röntgenquelle, Detektor-Lage und -Orientierung) werden für jedes Projektionsbild benötigt, da sonst bei der Rekonstruktion Artefakte entstehen können. Aufgrund der mechanischen Stabilität des C-Bogens wird eine Offline-Kalibrierung üblicherweise durchgeführt, damit die Projekionsparameter ermittelt werden können. Es wird dabei angenommen, dass Abweichungen von der Idealgeometrie reproduzierbar sind; stochastische Abweichungen (z. B. Vibrationen bei der Rotation) werden dabei nicht berücksichtigt. In dieser Arbeit präsentieren wir eine neue Methode zur geometrischen Online-Kalibrierung, die zusätzlich die stochastisch-mechanischen Abweichungen kompensiert. Die Qualität der Kalibrierung wird anhand von Simulations- und experimentellen Daten demonstriert

Variance-Based Iterative Image Reconstruction from Few Views in Limited-Angle C-Arm Computed Tomography

C-arm cone-beam computed tomography offers CT-like 3D imaging capabilities, but with the additional advantage of being appropriate for interventional suites. Due to the limitations of the data acquisition system, projections are oft acquired in a short scan angular range, resulting in significant artifacts, if conventional analytic formulas are applied. Furthermore, the presence of high-density objects, like metal parts, induces streak-like artifacts, which can obscure relevant anatomy. We present a new algorithm to reduce such artifacts and enhance the quality of reconstructed 3D volume. We make use of the variance of estimated voxel values over all projections to decrease the ground artifact level. The proposed algorithm is less sensitive to data truncation, and does not require explicit estimation of missing data. The number of required images is very low (up to 56 projections), which have several benefits, like significant reduction of patient dose and shortening of the acquisition time. The performance of the proposed method is demonstrated based on simulations and phantom data

Accurate Super-Resolution Reconstruction for CT and MR Images

The resolution and accuracy of medical images play an important role for early medical diagnosis, since a wrong resolution may increase the risk of making a poor decision. In practice, magnetic resonance and computed tomography images often suffer from anisotropic resolution, so that the image quality is high only within the slices. In this paper we propose a further development of a previously presented super-resolution approach, to reconstruct isotropic high resolution images from only two orthogonal low resolution data sets. Thereby, voxel uncertainties, which arise during image acquisition and preprocessing, are considered. Furthermore, an adapted inpainting method is introduced to ensure a better initial estimation of missing data. Reconstruction quality is also improved, by combining regional and local information. Experiments on synthetic and clinical data sets reveal significant improvement of image quality and accuracy, yielding better results when compared with conventional reconstruction approaches

Confidence map based super-resolution reconstruction

Magnetic Resonance Imaging and Computed Tomography usually provide highly anisotropic image data, so that the resolution in the slice-selection direction is poorer than in the in-plane directions. An isotropic high-resolution image can be reconstructed from two orthogonal scans of the same object. While combining the different data sets, all input data are usually equally weighted, without considering the fidelity level of each input information. In this paper we introduce a novel super-resolution method, which considers the fidelity level of each input data by introducing an adaptive confidence map. Experimental results on simulated and real data sets have shown the improved accuracy of reconstructed images, whose resolution approximate the original in-plane resolution in all directions. The quality of the reconstructed high resolution image was improved for noiseless input data sets, and even in the presence of different noise types with a low peak signal to noise ratio

Tracking von Instrumenten auf fluoroskopischen Aufnahmen für die navigierte Bronchoskopie

Intraoperative C-Bogen-Fluoroskopie dient bei der bronchoskopischen Biopsie zur Lokalisation des Bronchoskops und der Biospiezange innerhalb des Patiententhorax. Bei bekannter C-Bogen Pose ist es möglich, aus der 2D-Position der Instrumentenspitze auf der Fluoroskopie deren 3D-Position innerhalb des Bronchialbaums zu berechnen. Während die Pose mit Hilfe einer Markerplatte auf dem Patiententisch bestimmt werden kann, fehlt bisher eine automatische Verfolgung der Instrumentenspitze auf der kontinuierlichen Fluoroskopie. In dieser Arbeit wird eine solche Tracking-Methode vorgestellt und evaluiert. Erste Experimente an einem Bronchialbaum-Phantom lieferten sehr robuste und präzise Ergebnisse und auch die Echtzeitfähigkeit konnte gezeigt werden

Particle Path Segmentation: a Fast, Accurate, and Robust Method for Localization of Spherical Markers in Cone-beam CT Projections

Spherical fiducial markers are widely used for point-based registration of intra-operative 2D X-ray projections to preoperative 3D computed tomography images. The automatic localization of marker centers on X-rays speeds up the registration process and reduces the human error. However, a sub-pixel accurate localization of said centers is at present a challenging task, especially when fiducials overlap dense anatomical structures on the radiographs. In this paper, we propose a new method for automated and accurate detection of centers of fiducial markers in 2D projections, even in presence of structure overlapping. Several experiments confirm the high accuracy and robustness of the proposed algorithm achieving a localization error - mean (std) - equal to 0.059 (0.062) mm

Tracking von Instrumenten auf fluoroskopischen Aufnahmen für die navigierte Bronchoskopie

Intraoperative C-Bogen-Fluoroskopie dient bei der bronchoskopischen Biopsie zur Lokalisation des Bronchoskops und der Biospiezange innerhalb des Patiententhorax. Bei bekannter C-Bogen Pose ist es möglich, aus der 2D-Position der Instrumentenspitze auf der Fluoroskopie deren 3D-Position innerhalb des Bronchialbaums zu berechnen. Während die Pose mit Hilfe einer Markerplatte auf dem Patiententisch bestimmt werden kann, fehlt bisher eine automatische Verfolgung der Instrumentenspitze auf der kontinuierlichen Fluoroskopie. In dieser Arbeit wird eine solche Tracking-Methode vorgestellt und evaluiert. Erste Experimente an einem Bronchialbaum-Phantom lieferten sehr robuste und präzise Ergebnisse und auch die Echtzeitfähigkeit konnte gezeigt werden

Planning of High Precision Surgery at the Lateral Skull Base

Minimally traumatic surgery at the lateral skull base is currently far from being the standard in clinical routine. Drilling one or more linear paths towards the inner ear requires high accuracy. The project MUKNO aims at the development of tools and methods for allowing those minimally invasive approaches. For this, the errors of each single step of the surgery pipeline shall be quantified and minimized. All subsequent steps (e. g. surgery planning, navigation) rely on the acquired image data. Thus, it is crucial to provide such data with a sufficient accuracy. In this work, we present first results obtained in the project MUKNO. Here, one aspect is the high resolution image reconstruction from two orthogonal data sets. A second topic is the integration of a patient specific model of the lateral skull base into a virtual surgery simulation for the determination of possible drilling paths. For this, a first prototype of a planning tool is presented