We present a new steady-state imaging sequence, which simultaneously allows in a single acquisition the formation of two MR images with clearly different contrasts. The contrast of the first image is FISP-like, whereas the second image is strongly T2-weighted. In principle the T2 values in the image can be calculated from the combination of the first and second images. We also show calculated T2 images.

Surgical targeting of the incorrect vertebral level (“wrong-level” surgery) is among the more common wrong-site surgical errors, attributed primarily to a lack of uniquely identifiable radiographic landmarks in the mid-thoracic spine. Conventional localization method involves manual counting of vertebral bodies under fluoroscopy, is prone to human error, and carries additional time and dose. We propose an image registration and visualization system (referred to as LevelCheck), for decision support in spine surgery by automatically labeling vertebral levels in fluoroscopy using a GPU-accelerated, intensity-based 3D-2D (viz., CT-to-fluoroscopy) registration. A gradient information (GI) similarity metric and CMA-ES optimizer were chosen due to their robustness and inherent suitability for parallelization. Simulation studies involved 10 patient CT datasets from which 50,000 simulated fluoroscopic images were generated from C-arm poses selected to approximate C-arm operator and positioning variability. Physical experiments used an anthropomorphic chest phantom imaged under real fluoroscopy. The registration accuracy was evaluated as the mean projection distance (mPD) between the estimated and true center of vertebral levels. Trials were defined as successful if the estimated position was within the projection of the vertebral body (viz., mPD < 5mm). Simulation studies showed a success rate of 99.998% (1 failure in 50,000 trials) and computation time of 4.7 sec on a midrange GPU. Analysis of failure modes identified cases of false local optima in the search space arising from longitudinal periodicity in vertebral structures. Physical experiments demonstrated robustness of the algorithm against quantum noise and x-ray scatter. The ability to automatically localize target anatomy in fluoroscopy in near-real-time could be valuable in reducing the occurrence of wrong-site surgery while helping to reduce radiation exposure. The method is applicable beyond the specific case of vertebral labeling, since any structure defined in pre-operative (or intra-operative) CT or cone-beam CT can be automatically registered to the fluoroscopic scene.

In 2D Fourier imaging the normal Carr-Purcell multiple-echo sequence generally leads to center line and mirror artifacts caused by imperfect rotations by the rf pulses. We describe a method to avoid these distortions using a phase alternating-phase shift (PHAPS) sequence which also allows multiple-slice and multiple-echo imaging at the same time. Measuring phantoms with calibrated T2 values, we have shown that the PHAPS imaging sequence leads to an accuracy of quantitative T2 determinations of better than 10%. Contrast-enhanced images are presented which we calculated from multiple-echo images and extrapolated to arbitrary echotimes, including negative ones. We believe that these improvements in T2 imaging will result in a significant reduction of patient investigation time in magnetic resonance imaging.

3D reconstruction of arterial vessels from planar radiographs obtained at several angles around the object has gained increasing interest. The motivating application has been interventional angiography. In order to obtain a three-dimensional reconstruction from a C-arm mounted X-Ray Image Intensifier (XRII) traditionally the trajectory of the source and the detector system is characterized and the pixel size is estimated. The main use of the imaging geometry characterization is to provide a correct 3D-2D mapping between the 3D voxels to be reconstructed and the 2D pixels on the radiographic images. We propose using projection matrices directly in a voxel driven backprojection for the reconstruction as opposed to that of computing all the geometrical parameters, including the imaging parameters. We discuss the simplicity of the entire calibration-reconstruction process, and the fact that it makes the computation of the pixel size, source to detector distance, and other explicit imaging parameters unnecessary. A usual step in the reconstruction is sinogram weighting, in which the projections containing corresponding data from opposing directions have to be weighted before they are filtered and backprojected into the object space. The rotation angle of the C-arm is used in the sinogram weighting. This means that the C-arm motion parameters must be computed from projection matrices. The numerical instability associated with the decomposition of the projection matrices into intrinsic and extrinsic parameters is discussed in the context. The paper then describes our method of computing motion parameters without matrix decomposition. Examples of the calibration results and the associated volume reconstruction are also shown.

Recently there has been increasing interest in obtaining three-dimensional reconstructions of arterial vessels from multiple planar radiographs (obtained at angles around the object). Interventional angiography is the motivating application behind this research. Different methods have been proposed to acquire the planar data such as a gantry mounted x-ray image intensifier (XRII) or a C-arm mounted XRII. In order to obtain a threedimensional reconstruction from a C-arm mounted XRII the trajectory of the source and detector system must be characterized.We have designed a calibration system that provides the necessary trajectory information using uniquely identifiable markers positioned on a cylinder. This calibration ring is to be placed around the patient's head, and consists of steel balls positioned in a predefined arrangement on a cylindrical acrylic support. The balls are arranged such that calibration can be done from almost any partial view, allowing reconstruction of a region of interest (ROl). Steel balls are placed around an acrylic cylinder, restricted to a band approximately 8.5 mm wide, thereby obscuring only a small fraction of the image. In this case the radiograph includes the region of interest (ROT) as well as a partial view of the calibration ring. This enables us to recover the geometry of X-ray imaging system from each individual frame. We call this process "dynamic calibration" as opposed to "off-line" calibration procedures which try to characterize the motion of C-arm before introducing the patient.

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X-ray images are widely used during surgery for long bone fracture fixation. Mobile C-arms provide X-ray images which are used to determine the quality of trauma reduction, i.e. the extremity length and mechanical axis of long bones. Standard X-ray images have a narrow field of view and can not visualize the entire long bone on a single image. In this paper, we propose a novel method to generate panoramic X-ray images in real time by using the previously introduced Camera Augmented Mobile C-arm [1]. This advanced mobile C-arm system acquires registered X-ray and optical images by construction, which facilitates the generation of panoramic X-ray images based on first stitching the optical images and then embedding the X-ray images. We additionally introduce a method to reduce the parallax effect that leads to the blurring and measurement error on panoramic X-ray images. Visual marker tracking is employed to automatically stitch the sequence of video images and to rectify images. Our proposed method is suitable for intra-operative usage generating panoramic X-ray images, which enable metric measurements, with less radiation and without requirement of fronto-parallel setup and overlapping X-ray images. The results show that the panoramic X-ray images generated by our method are accurate enough (errors less than 1%) for metric measurements and suitable for many clinical applications in trauma reduction.

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