Fast DRR generation for 2D to 3D registration on GPUs.

PURPOSE: The generation of digitally reconstructed radiographs (DRRs) is the most time consuming step on the CPU in intensity based two-dimensional x-ray to three-dimensional (CT or 3D rotational x-ray) medical image registration, which has application in several image guided interventions. This work presents optimized DRR rendering on graphical processor units (GPUs) and compares performance achievable on four commercially available devices. METHODS: A ray-cast based DRR rendering was implemented for a 512 × 512 × 72 CT volume. The block size parameter was optimized for four different GPUs for a region of interest (ROI) of 400 × 225 pixels with different sampling ratios (1.1%-9.1% and 100%). Performance was statistically evaluated and compared for the four GPUs. The method and the block size dependence were validated on the latest GPU for several parameter settings with a public gold standard dataset (512 × 512 × 825 CT) for registration purposes. RESULTS: Depending on the GPU, the full ROI is rendered in 2.7-5.2 ms. If sampling ratio of 1.1%-9.1% is applied, execution time is in the range of 0.3-7.3 ms. On all GPUs, the mean of the execution time increased linearly with respect to the number of pixels if sampling was used. CONCLUSIONS: The presented results outperform other results from the literature. This indicates that automatic 2D to 3D registration, which typically requires a couple of hundred DRR renderings to converge, can be performed quasi on-line, in less than a second or depending on the application and hardware in less than a couple of seconds. Accordingly, a whole new field of applications is opened for image guided interventions, where the registration is continuously performed to match the real-time x-ray.

A new system for computer-aided preoperative planning and intraoperative navigation during corrective jaw surgery.

A new system for computer-aided corrective surgery of the jaws has been developed and introduced clinically. It combines three-dimensional (3-D) surgical planning with conventional dental occlusion planning. The developed software allows simulating the surgical correction on virtual 3-D models of the facial skeleton generated from computed tomography (CT) scans. Surgery planning and simulation include dynamic cephalometry, semi-automatic mirroring, interactive cutting of bone and segment repositioning. By coupling the software with a tracking system and with the help of a special registration procedure, we are able to acquire dental occlusion plans from plaster model mounts. Upon completion of the surgical plan, the setup is used to manufacture positioning splints for intraoperative guidance. The system provides further intraoperative assistance with the help of a display showing jaw positions and 3-D positioning guides updated in real time during the surgical procedure. The proposed approach offers the advantages of 3-D visualization and tracking technology without sacrificing long-proven cast-based techniques for dental occlusion evaluation. The system has been applied on one patient. Throughout this procedure, we have experienced improved assessment of pathology, increased precision, and augmented control.

Development of a force amplitude- and location-sensing device designed to improve the ligament balancing procedure in TKA.

To improve the ligament balancing procedure during total knee arthroplasty a force-sensing device to intraoperatively measure knee joint forces and moments has been developed. It consists of two sensitive plates, one for each condyle, a tibial base plate and a set of spaces to adapt the device thickness to the patient-specific tibiofemoral gap. Each sensitive plate is equipped with three deformable bridges instrumented with thick-film piezoresistive sensors, which allow accurate measurements of the amplitude and location of the tibiofemoral contact forces. The net varus-valgus moment is then computed to characterize the ligamentous imbalance. The developed device has a measurement range of 0-500 N and an intrinsic accuracy of 0.5% full scale. Experimental trials on a plastic knee joint model and on a cadaver specimen demonstrated the proper function of the device in situ. The results obtained indicated that the novel force-sensing device has an appropriate range of measurement and a strong potential to offer useful quantitative information and effective assistance during the ligament balancing procedure in total knee arthroplasty.

Improved targeting device and computer navigation for accurate placement of brachytherapy needles.

Successful treatment of skull base tumors with interstitial brachytherapy requires high targeting accuracy for the brachytherapy needles to avoid harming vital anatomical structures. To enable safe placement of the needles in this area, we developed an image-based planning and navigation system for brachytherapy, which includes a custom-made mechanical positioning arm that allows rough and fine adjustment of the needle position. The fine-adjustment mechanism consists of an XYZ microstage at the base of the arm and a needle holder with two fine-adjustable inclinations. The rotation axes of the inclinations cross at the tip of the needle so that the inclinational adjustments do not interfere with the translational adjustments. A vacuum cushion and a noninvasive fixation frame are used for the head immobilization. To avoid mechanical bending of the needles due to the weight of attached tracking markers, which would be detrimental for targeting accuracy, only a single LED marker on the tail of the needle is used. An experimental phantom-based targeting study with this setup demonstrated that a positioning accuracy of 1.4 mm (rms) can be achieved. The study showed that the proposed setup allows brachytherapy needles to be easily aligned and inserted with high targeting accuracy according to a preliminary plan. The achievable accuracy is higher than if the needles are inserted manually. The proposed system can be linked to a standard afterloader and standard dosimetry planning module. The associated additional effort is reasonable for the clinical practice and therefore the proposed procedure provides a promising tool for the safe treatment of tumors in the skull base area.

Automatic method to assess local CT-MR imaging registration accuracy on images of the head.

BACKGROUND AND PURPOSE: Precise registration of CT and MR images is crucial in many clinical cases for proper diagnosis, decision making or navigation in surgical interventions. Various algorithms can be used to register CT and MR datasets, but prior to clinical use the result must be validated. To evaluate the registration result by visual inspection is tiring and time-consuming. We propose a new automatic registration assessment method, which provides the user a color-coded fused representation of the CT and MR images, and indicates the location and extent of poor registration accuracy. METHODS: The method for local assessment of CT-MR registration is based on segmentation of bone structures in the CT and MR images, followed by a voxel correspondence analysis. The result is represented as a color-coded overlay. The algorithm was tested on simulated and real datasets with different levels of noise and intensity non-uniformity. RESULTS: Based on tests on simulated MR imaging data, it was found that the algorithm was robust for noise levels up to 7% and intensity non-uniformities up to 20% of the full intensity scale. Due to the inability to distinguish clearly between bone and cerebro-spinal fluids in the MR image (T1-weighted), the algorithm was found to be optimistic in the sense that a number of voxels are classified as well-registered although they should not. However, nearly all voxels classified as misregistered are correctly classified. CONCLUSION: The proposed algorithm offers a new way to automatically assess the CT-MR image registration accuracy locally in all the areas of the volume that contain bone and to represent the result with a user-friendly, intuitive color-coded overlay on the fused dataset.

New method to assess the registration of CT-MR images of the head.

Due to their complementary information content, both x-ray computed tomography (CT) and magnetic resonance (MR) imaging are employed in certain clinical cases to improve the understanding of pathology involved. o spatially relate the two datasets, image registration and image fusion are employed. However, registration errors, either global or local, are common and are nonuniform within the image volume. In this paper, we propose a new algorithm that assesses the quality of the registration locally within the CT-MR volume and provides visual, color-coded feedback to the user about the location and extent of good and bad correspondence between the two images. The proposed registration assessment algorithm is based on a correspondence analysis of bone structures in the CT and MR images. For that purpose, a custom segmentation algorithm for bone in MR images has been developed that is based on a stochastic threshold computation method. This segmentation method for MR images and the CT-MR registration assessment algorithm were validated on simulated MR datasets and real CT-MR image pairs of the head. Some partial-volume effects occur at the borders of the bone structures and at the bone interfaces with air, which cannot be separated from bone in the MR image. The presented assessment method of CT-MR image registration offers the user a new tool to evaluate the overall and local quality of the registration. With this information, the user does not have to blindly trust the fused CT-MR datasets but can easily identify areas of inaccurate correspondence. The application of the algorithm is so far limited to T1-weighted MR and CT images of the head area.

Transcutaneous functional electrical stimulator "Compex Motion".

Research groups in the field of functional electrical stimulation (FES) are often confronted with the fact that existing and commercially available FES stimulators do not provide sufficient flexibility and cannot be used to perform different FES tasks. The lack of flexibility of the commercial systems until now forced various FES research teams to develop their own stimulators. This paper presents a newly developed firmware and graphical programming software for the commercial Compex 2 stimulator which enhances the versatility and capabilities of the stimulator from a medical and therapeutic device to a neuroprosthesis and research tool. The new stimulator, called Compex Motion, can now be used to develop various custom-made neuroprostheses, neurological assessment devices, muscle exercise systems, and experimental setups for physiological studies. It can be programmed to generate any arbitrary stimulation sequence that can be controlled or regulated by various external sensors, sensory systems, or laboratory equipment. By interconnecting two or more Compex Motion stimulators, the number of stimulation channels can be increased to multiples of four channels, 8, 12, 16, 20, and so forth. The stimulation sequences and the control strategies are programmed and stored on exchangeable credit card-sized memory chip cards. The stimulator has four biphasic current-regulated stimulation channels and two general purpose analog input channels that can be configured to measure the output voltage of a variety of sensors such as goniometers, inclinometers, gyroscopes, or electromyographic (EMG) sensors. For real-time EMG control of the stimulation patterns, an EMG processing algorithm with software stimulation artifact blanking was implemented. The Compex Motion stimulator is manufactured by the Swiss company Compex SA and is currently undergoing clinical trials.