Advancements and Breakthroughs in Ultrasound Imaging

Ultrasonic imaging is a powerful diagnostic tool available to medical practitioners, engineers and researchers today. Due to the relative safety, and the non-invasive nature, ultrasonic imaging has become one of the most rapidly advancing technologies. These rapid advances are directly related to the parallel advancements in electronics, computing, and transducer technology together with sophisticated signal processing techniques. This book focuses on state of the art developments in ultrasonic imaging applications and underlying technologies presented by leading practitioners and researchers from many parts of the world

Automatic visual recognition using parallel machines

Invariant features and quick matching algorithms are two major concerns in the area of automatic visual recognition. The former reduces the size of an established model database, and the latter shortens the computation time. This dissertation, will discussed both line invariants under perspective projection and parallel implementation of a dynamic programming technique for shape recognition. The feasibility of using parallel machines can be demonstrated through the dramatically reduced time complexity. In this dissertation, our algorithms are implemented on the AP1000 MIMD parallel machines. For processing an object with a features, the time complexity of the proposed parallel algorithm is O(n), while that of a uniprocessor is O(n2). The two applications, one for shape matching and the other for chain-code extraction, are used in order to demonstrate the usefulness of our methods. Invariants from four general lines under perspective projection are also discussed in here. In contrast to the approach which uses the epipolar geometry, we investigate the invariants under isotropy subgroups. Theoretically speaking, two independent invariants can be found for four general lines in 3D space. In practice, we show how to obtain these two invariants from the projective images of four general lines without the need of camera calibration. A projective invariant recognition system based on a hypothesis-generation-testing scheme is run on the hypercube parallel architecture. Object recognition is achieved by matching the scene projective invariants to the model projective invariants, called transfer. Then a hypothesis-generation-testing scheme is implemented on the hypercube parallel architecture

Comparison of diffusion tensor imaging by cardiovascular magnetic resonance and gadolinium enhanced 3D image intensity approaches to investigation of structural anisotropy in explanted rat hearts

Background: Cardiovascular magnetic resonance (CMR) can through the two methods 3D FLASH and diffusion tensor imaging (DTI) give complementary information on the local orientations of cardiomyocytes and their laminar arrays. Methods: Eight explanted rat hearts were perfused with Gd-DTPA contrast agent and fixative and imaged in a 9.4T magnet by two types of acquisition: 3D fast low angle shot (FLASH) imaging, voxels 50 × 50 × 50 μm, and 3D spin echo DTI with monopolar diffusion gradients of 3.6 ms duration at 11.5 ms separation, voxels 200 × 200 × 200 μm. The sensitivity of each approach to imaging parameters was explored. Results:The FLASH data showed laminar alignments of voxels with high signal, in keeping with the presumed predominance of contrast in the interstices between sheetlets. It was analysed, using structure-tensor (ST) analysis, to determine the most (v 1 ST ), intermediate (v 2 ST ) and least (v 3 ST ) extended orthogonal directions of signal continuity. The DTI data was analysed to determine the most (e 1 DTI ), intermediate (e 2 DTI ) and least (e 3 DTI ) orthogonal eigenvectors of extent of diffusion. The correspondence between the FLASH and DTI methods was measured and appraised. The most extended direction of FLASH signal (v 1 ST ) agreed well with that of diffusion (e 1 DTI ) throughout the left ventricle (representative discrepancy in the septum of 13.3 ± 6.7°: median ± absolute deviation) and both were in keeping with the expected local orientations of the long-axis of cardiomyocytes. However, the orientation of the least directions of FLASH signal continuity (v 3 ST ) and diffusion (e 3 ST ) showed greater discrepancies of up to 27.9 ± 17.4°. Both FLASH (v 3 ST ) and DTI (e 3 DTI ) where compared to directly measured laminar arrays in the FLASH images. For FLASH the discrepancy between the structure-tensor calculated v 3 ST and the directly measured FLASH laminar array normal was of 9 ± 7° for the lateral wall and 7 ± 9° for the septum (median ± inter quartile range), and for DTI the discrepancy between the calculated v 3 DTI and the directly measured FLASH laminar array normal was 22 ± 14° and 61 ± 53.4°. DTI was relatively insensitive to the number of diffusion directions and to time up to 72 hours post fixation, but was moderately affected by b-value (which was scaled by modifying diffusion gradient pulse strength with fixed gradient pulse separation). Optimal DTI parameters were b = 1000 mm/s2 and 12 diffusion directions. FLASH acquisitions were relatively insensitive to the image processing parameters explored. Conclusions: We show that ST analysis of FLASH is a useful and accurate tool in the measurement of cardiac microstructure. While both FLASH and the DTI approaches appear promising for mapping of the alignments of myocytes throughout myocardium, marked discrepancies between the cross myocyte anisotropies deduced from each method call for consideration of their respective limitations

Mathematics and Digital Signal Processing

Modern computer technology has opened up new opportunities for the development of digital signal processing methods. The applications of digital signal processing have expanded significantly and today include audio and speech processing, sonar, radar, and other sensor array processing, spectral density estimation, statistical signal processing, digital image processing, signal processing for telecommunications, control systems, biomedical engineering, and seismology, among others. This Special Issue is aimed at wide coverage of the problems of digital signal processing, from mathematical modeling to the implementation of problem-oriented systems. The basis of digital signal processing is digital filtering. Wavelet analysis implements multiscale signal processing and is used to solve applied problems of de-noising and compression. Processing of visual information, including image and video processing and pattern recognition, is actively used in robotic systems and industrial processes control today. Improving digital signal processing circuits and developing new signal processing systems can improve the technical characteristics of many digital devices. The development of new methods of artificial intelligence, including artificial neural networks and brain-computer interfaces, opens up new prospects for the creation of smart technology. This Special Issue contains the latest technological developments in mathematics and digital signal processing. The stated results are of interest to researchers in the field of applied mathematics and developers of modern digital signal processing systems

Studies of inspection algorithms and associated microprogrammable hardware implementations

This work is concerned with the design and development of real-time algorithms for industrial inspection applications. Rather than implement algorithms in dedicated hardware, microprogrammable machines were considered essential in order to maintain flexibility. After a survey of image pattern recognition where algorithms applicable to real-time use are cited, this thesis presents industrial inspection algorithms that locate and scrutinise actual manufactured products. These are fast and robust - a necessary requirement in industrial environments. The National Physical Laboratory have developed a Linear Array Processor (LAP) specifically designed for industrial recognition work. As with most array processors, the LAP has a greater performance than conventional processors, yet is strictly limited to parallel algorithms for optimum performance. It was therefore necessary to incorporate sequentialism into the design of a multiprocessor system. A microcoded bit-slice Sequential Image Processor (SIP) has been designed and built at RHBNC in conjunction with the NPL. This was primarily intended as a post-processor for the LAP based on the VMEbus but in fact has proved its usefulness as a stand-alone processor. This is described along with an assembler written for SIP which translates assembly language mnemonics to microcode. This work, which includes a review of current architectures, leads to the specification of a hybrid (SIMD/NIMD) architecture consisting of multiple autonomous sequential processors. This involves an analysis of various configurations and entails an investigation of the source of bottlenecks within each design. Such systems require a significant amount of interprocessor communication: methods for achieving this are discussed, some of which have only become practical with the decrease incost of electronic components. This eventually leads to a system for which algorithm execution speed increases approximately linearly with the number of processors. The algorithms described in earlier chapters are examined on the system and the practicalities of such a design are analysed in detail. Overall, this thesis has arrived at designs of programmable real-time inspection systems, and has obtained guidelines which will help with the implementation of future inspection systems.<p

Visual inspection : image sampling, algorithms and architectures

The thesis concerns the hexagonal sampling of images, the processing of industrially derived images, and the design of a novel processor element that can be assembled into pipelines to effect fast, economic and reliable processing. A hexagonally sampled two dimensional image can require 13.4% fewer sampling points than a square sampled equivalent. The grid symmetry results in simpler processing operators that compute more efficiently than square grid operators. Computation savings approaching 44% arc demonstrated. New hexagonal operators arc reported including a Gaussian smoothing filter, a binary thinner, and an edge detector with comparable accuracy to that of the Sobel detector. The design of hexagonal arrays of sensors is considered. Operators requiring small local areas of support are shown to be sufficient for processing controlled lighting and industrial images. Case studies show that small features in hexagonally processed images maintain their shape better, and that processes can tolerate a lower signal to noise ratio, than that for equivalent square processed images. The modelling of small defects in surfaces has been studied in depth. The flexible programmable processor element can perform the low level local operators required for industrial image processing on both square and hexagonal grids. The element has been specified and simulated by a high level computer program. A fast communication channel allows for dynamic reprogramming by a control computer, and the video rate element can be assembled into various pipeline architectures, that may eventually be adaptively controlled

Temporal unpredictability detection of real-time video sequence

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