KEYWORDS: Transducers, 3D acquisition, Ultrasonography, 3D image processing, Data acquisition, Error analysis, 3D image reconstruction, 3D metrology, 3D modeling, Visualization
Three-dimensional (3D) ultrasound data are acquired mostly using a dedicated mechanical probe that houses a 1D array
transducer. This 1D transducer swivels back and forth continuously in the elevation direction (continuous scanning) for
fast acquisition. When 3D ultrasound data are acquired via continuous scanning but the continuous motion of a
transducer is not taken into account during reconstruction, the reconstructed volume contains error. In this study, we
systematically analyzed this error, which is a complex function of many parameters. The error increases when the
transducer angular speed (ω) increases. Also, it varies depending on the voxel location inside an acquired volume. The
mean error is calculated by averaging the errors at all acquired voxel locations. With a 60-degree volume angle, a 60-degree sector angle, 12-cm scan depth and 48 transmit beams per slice, the mean error is 5.3 mm when ω is 0.6
degrees/ms. When ω is reduced to 0.1 degrees/ms, the mean error decreases to 0.81 mm. We also assessed the impact
of this error on the reconstructed images of a 3D phantom using simulation. At high angular speeds, the error in
reconstructed images becomes noticeable and results in missing parts, geometric distortion and lowered image quality.
KEYWORDS: Ultrasonography, Visualization, Volume rendering, Digital video recorders, 3D image processing, Image quality, Boxcar filters, Signal processing, Data acquisition, Algorithm development
Three-dimensional (3D) ultrasound has become a useful tool in cardiac imaging, OB/GYN and other clinical
applications. It enables clinicians to visualize the acquired volume and/or planes that are not easily accessible using 2D
ultrasound, in addition to providing an intuitive understanding of the structural anatomy in three dimensions. One
effective way to examine the acquired volumetric data is by clipping away parts of the volume using cross-sectional cuts
to reveal the underlying anatomy masked by other structures. Ideally, such boundaries should reflect the orientation and
location of the clip surfaces without altering the information content of the original data. Because of the artificial surface
introduced by the clip boundary, shading employed to enhance the surfaces of the object gets modified, resulting in
inconsistent shading and noticeable artifacts in the case of ultrasound data. Consistent shading of clip surfaces was
previously studied for graphics hardware-based volume rendering, and an algorithm was developed and demonstrated in
MRI, CT and non-medical datasets. However, that algorithm cannot be applied directly to fast software-based rendering
approaches such as the shear-warp algorithm. Furthermore, ultrasound data require a different clipping approach due to
their fuzzy nature, lower signal-to-noise ratios, and real-time requirements. In this paper, we present a software-based
volume clipping technique that can effectively and efficiently overcome the difficulties associated with the shading of
the clip boundaries in ultrasound data using shear-warp. Our technique improves the viewer's comprehension of the clip
boundary without altering the original information content within the volume. The method has been implemented on
programmable processors while maintaining the interactive speed in rendering.
KEYWORDS: Volume rendering, Ultrasonography, Image quality, Opacity, Digital signal processing, Signal processing, 3D image processing, Medical imaging, Computed tomography, Computing systems
Volume rendering in 3D ultrasound is a challenging task due to the large amount of computation required for real-time rendering. The shear-warp algorithm has been traditionally used for 3D ultrasound rendering for its effectiveness in lowering computing cost. However, this lowered computing cost does come at the price of reduced image quality due to (a) the presence of final warp interpolation, which smoothes out fine details and (b) sampling only at discrete slice locations, which introduces aliasing, e.g., staircase artifacts. For 3D ultrasound, we have merged pre-integration with the shear-image-order algorithm to overcome both limitations of shear-warp while still enjoying the computational savings. Pre-integration overcomes the aliasing artifacts while shear-image-order preserves details. We have also developed a technique to integrate shading coefficient into pre-integrated rendering. This pre-integrated shear-image-order algorithm, with slightly higher computation than what is required to support the shear-warp algorithm, improves the quality of the rendered image significantly. In this paper, we discuss the pre-integrated shear-image-order algorithm and present the results of subjective quality evaluation on several data sets. We have also analyzed how this algorithm can be implemented on an advanced digital signal processor (DSP) to achieve real-time performance.
Texas Instruments recently introduced its latest C6000 family DSP core; TMS320C64x. C64x is a VLIW DSP core with eight 32-bit functional units, two levels of on-chip memory and a programmable Direct Memory Access (DMA) controller. We have developed about 25 image/video computing functions and have assessed its performance and suitability in image/video computing. We present some of these results along with an example on how we mapped image warping optimally onto the C64x core. C64x, although a 32-bit architecture, has a throughput similar to that of 64-bit architectures. It is powerful due to its large and multi-level on-chip memory, a number of available functional units, high clock frequency, and ease of programming.
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