Bone enhancement in ultrasound using local spectrum variations for guiding percutaneous scaphoid fracture fixation procedures.

PURPOSE: The scaphoid bone is the most frequently fractured bone in the wrist. When fracture fixation is indicated, a screw is inserted into the bone either in an open surgical procedure or percutaneously under fluoroscopic guidance. Due to the complex geometry of the wrist, fracture fixation is a challenging task. Fluoroscopic guidance exposes both the patient and the physician to ionizing radiation. Ultrasound-based guidance has been suggested as a real-time, radiation-free alternative. The main challenge of using ultrasound is the difficulty in interpreting the images due to the low contrast and noisy nature of the data. METHODS: We propose a bone enhancement method that exploits local spectrum features of the ultrasound image. These features are utilized to design a set of quadrature band-pass filters and subsequently estimate the local phase symmetry, where high symmetry is expected at the bone locations. We incorporate the shadow information below the bone surfaces to further enhance the bone responses. The extracted bone surfaces are then used to register a statistical wrist model to ultrasound volumes, allowing the localization and interpretation of the scaphoid bone in the volumes. RESULTS: Feasibility experiments were performed using phantom and in vivo data. For phantoms, we obtain a surface distance error 1.08 mm and an angular deviation from the main axis of the scaphoid bone smaller than 5°, which are better compared to previously presented approaches. CONCLUSION: The results are promising for further development of a surgical guidance system to enable accurate anatomy localization for guiding percutaneous scaphoid fracture fixations.

Direct and gradient-based average strain estimation by using weighted nearest neighbor cross-correlation peaks.

In this paper, two novel approaches, gradient-based and direct strain estimation techniques, are proposed for high-quality average strain imaging incorporating a cost function maximization. Stiffness typically is a continuous function. Consequently, stiffness of proximal tissues is very close to that of the tissue corresponding to a given data window. Hence, a cost function is defined from exponentially weighted neighboring pre- and post-compression RF echo normalized cross-correlation peaks in the lateral (for displacement estimation) or in both the axial and the lateral (for direct strain estimation) directions. This enforces a controlled continuity in displacement/strain and average displacement/strain is calculated from the corresponding maximized cost function. Axial stress causes lateral shift in the tissue. Therefore, a 1-D post-compression echo segment is selected by incorporating Poisson's ratio. Two stretching factors are considered simultaneously in gradient-based strain estimation that allow imaging the lesions properly. The proposed time-domain gradient-based and direct-strain-estimation-based algorithms demonstrate significantly better performance in terms of elastographic signal-to-noise ratio (SNRe), elastographic contrast-to-noise ratio (CNRe), peak signal-to-noise ratio (PSNR), and mean structural similarity (MSSIM) than the other reported time-domain gradient-based and direct-strain-estimation techniques in finite element modeling (FEM) simulation and phantom experiments. For example, in FEM simulation, it has been found that the proposed direct strain estimation method can improve up to approximately 2.49 to 8.71, 2.2 to 6.63, 1.5 to 5, and 1.59 to 2.45 dB in the SNRe, CNRe, PSNR, and MSSIM compared with the traditional direct strain estimation method, respectively, and the proposed gradient-based algorithm demonstrates 2.99 to 16.26, 18.74 to 23.88, 3 to 9.5, and 0.6 to 5.36 dB improvement in the SNRe, CNRe, PSNR, and MSSIM, respectively, compared with a recently reported time-domain gradient-based technique. The range of improvement as noted above is for low to high applied strains. In addition, the comparative results using the in vivo breast data (including malignant or benign masses) also show that the lesion size is better defined by the proposed gradient-based average strain estimation technique.

Removal of ring artifacts in CT imaging through detection and correction of stripes in the sinogram.

Due to malfunctioning and mis-calibration of cells in digital x-ray detectors as well as impurities on the scintillator screens, stripe artifacts arise in the sinogram which in turn generate ring artifacts in the reconstructed x-ray computed tomography images. In this paper, a novel technique is proposed for the detection and removal of stripe artifacts in a sinogram with a view to suppress the ring artifacts from the tomographic images. To accurately detect the stripe creating pixels using a derivative-based algorithm, at first the sinogram is windowed to create a sub-sinogram by keeping the pixel of examination at the center position in the sub-sinogram. The other pixels in the sub-sinogram are selected from a polyphase component of the sinogram. A new mathematical index is proposed here to isolate the strong and weak ring-generating stripes from the good ones. For the correction of strong ring artifacts resulting from the defective detector elements and dusty scintillator crystals, 2D variable window moving average and weighted moving average filters are proposed in this work. On the other hand, a conventionally trusted constant bias correction scheme is adopted to correct the responses of the mis-calibrated detector elements. To evaluate and compare the performance of the proposed algorithm, real micro-CT images acquired from two flat panel detectors under different operating conditions are used. Experimental results show that the proposed method can remove ring artifacts more effectively without imparting noticeable distortion in the image as compared to a recently reported technique in the literature.