An Optimized Spline-Based Registration of a 3D CT to a Set of C-Arm Images

We have developed an algorithm for the rigid-body registration of a CT volume to a set of C-arm images. The algorithm uses a gradient-based iterative minimization of a least-squares measure of dissimilarity between the C-arm images and projections of the CT volume. To compute projections, we use a novel method for fast integration of the volume along rays. To improve robustness and speed, we take advantage of a coarse-to-fine processing of the volume/image pyramids. To compute the projections of the volume, the gradient of the dissimilarity measure, and the multiresolution data pyramids, we use a continuous image/volume model based on cubic B-splines, which ensures a high interpolation accuracy and a gradient of the dissimilarity measure that is well defined everywhere. We show the performance of our algorithm on a human spine phantom, where the true alignment is determined using a set of fiducial markers

Pivot calibration concept for sensor attached mobile c-arms

Medical augmented reality has been actively studied for decades and many methods have been proposed torevolutionize clinical procedures. One example is the camera augmented mobile C-arm (CAMC), which providesa real-time video augmentation onto medical images by rigidly mounting and calibrating a camera to the imagingdevice. Since then, several CAMC variations have been suggested by calibrating 2D/3D cameras, trackers, andmore recently a Microsoft HoloLens to the C-arm. Different calibration methods have been applied to establishthe correspondence between the rigidly attached sensor and the imaging device. A crucial step for these methodsis the acquisition of X-Ray images or 3D reconstruction volumes; therefore, requiring the emission of ionizingradiation. In this work, we analyze the mechanical motion of the device and propose an alternatative methodto calibrate sensors to the C-arm without emitting any radiation. Given a sensor is rigidly attached to thedevice, we introduce an extended pivot calibration concept to compute the fixed translation from the sensor tothe C-arm rotation center. The fixed relationship between the sensor and rotation center can be formulated as apivot calibration problem with the pivot point moving on a locus. Our method exploits the rigid C-arm motiondescribing a Torus surface to solve this calibration problem. We explain the geometry of the C-arm motion andits relation to the attached sensor, propose a calibration algorithm and show its robustness against noise, as wellas trajectory and observed pose density by computer simulations. We discuss this geometric-based formulationand its potential extensions to different C-arm applications.Comment: Accepted for Image-Guided Procedures, Robotic Interventions, and Modeling 2020, Houston, TX, US

Development and evaluation of image-guided neuroendoscopy, with investigation of post-imaging brain distortion and accuracy of frameless stereotaxy

Neuroendoscopy enables a surgeon to operate deep within the brain whilst limiting morbidity through a minimally invasive approach. Technical advances in illumination, instrumentation and camera design, along with evidence for improved clinical outcome, have increased the indications for this technique and have ensured widespread popularity. However, broader application of neuroendoscopy is restricted by the necessity for direct vision of targets and by spatial disorientation. The aim of this investigation was to overcome these limitations by combining neuronavigation with neuroendoscopy to develop Image-Guided Neuroendoscopy (IGN). The strategy adopted for this was firstly to select, assess and validate a neuronavigation system, secondly to develop methods of endoscope tracking and frameless stereotactic implantation. Thirdly, to assess the impact of post-imaging brain distortion upon neuronavigation, fourthly to correct distortion of the endoscope image and finally to assess the use of graphics overlay in IGN. Laboratory phantom accuracy assessments revealed a mean point localisation error for the navigation system pointers of0.8mm (SD 0.4mm) with CT imaging, for the tracked endoscope of 1.5mm (SD 0.8mm) and for frameless stereotaxy of 1.3mm (SD 0.6mm). An in vivo study revealed a mean Euclidean error of 4.8mm (SD 2.0mm) for frame less stereotactic biopsy. The navigation system was evaluated through a clinical series of 100 cases, the frameless stereotactic technique was employed in 21 brain biopsy procedures and IGN evaluated in 5 procedures. The magnitude of post-imaging brain distortion was determined and correlations discovered with pre-operative image characteristics. The conclusions of this thesis are that IGN can be accomplished with acceptable accuracy, including frameless stereotactic implantation, and that the impact of postimaging brain distortion will not negate the value of IGN in most cases. Thus, the method developed for IGN has overcome both major constraints of neuroendoscopy, enabling endoscopic surgery to pass through and beyond the ventricular wall, to be undertaken safely in cases with distorted anatomy and opening the potential for wider application of these minimally invasive techniques