Multiple template matching using the expansion filter

The paper describes a multiple-template generalization of a newly developed approach for template matching by signal expansion into a set of non-orthogonal template-similar basis functions. The single-template method is proven to be equivalent to "restoration" of undegraded images using the Wiener filter and optimizes a new and more practically defined matching quality criterion that the authors call discriminative signal-to-noise ratio (DSNR). Compared to the widely used matched filtering approach (also known as correlation matching) which is based an projection, expansion matching is based on decomposition and is shown to be more robust in conditions of noise, superposition and severe occlusion. In the paper, the authors extend the DSNR optimization approach to include more than one template. The generalized expansion filter presented is optimal in terms of DSNR and can be designed to elicit any desired response for each of the templates, while optimizing the DSNR criterion. The approach considers additive noise as a parameter and leads to a general formulation, of which many previous approaches (such as the synthetic discriminant function) form special cases. In the case of a single template, the formulation reverts to the previously mentioned Wiener restoration filter

Object Recognition

Vision-based object recognition tasks are very familiar in our everyday activities, such as driving our car in the correct lane. We do these tasks effortlessly in real-time. In the last decades, with the advancement of computer technology, researchers and application developers are trying to mimic the human's capability of visually recognising. Such capability will allow machine to free human from boring or dangerous jobs

Uniform framework for the objective assessment and optimisation of radiotherapy image quality

Image guidance has rapidly become central to current radiotherapy practice. A uniform framework is developed for evaluating image quality across all imaging modalities by modelling the ‘universal phantom’: breaking any phantom down into its constituent fundamental test objects and applying appropriate analysis techniques to these through the construction of an automated analysis tree. This is implemented practically through the new software package ‘IQWorks’ and is applicable to both radiotherapy and diagnostic imaging. For electronic portal imaging (EPI), excellent agreement was observed with two commercial solutions: the QC-3V phantom and PIPS Pro software (Standard Imaging) and EPID QC phantom and epidSoft software (PTW). However, PIPS Pro’s noise correction strategy appears unnecessary for all but the highest frequency modulation transfer function (MTF) point and its contrast to noise ratio (CNR) calculation is not as described. Serious flaws identified in epid- Soft included erroneous file handling leading to incorrect MTF and signal to noise ratio (SNR) results, and a sensitivity to phantom alignment resulting in overestimation of MTF points by up to 150% for alignment errors of only ±1 pixel. The ‘QEPI1’ is introduced as a new EPI performance phantom. Being a simple lead square with a central square hole it is inexpensive and straightforward to manufacture yet enables calculation of a wide range of performance metrics at multiple locations across the field of view. Measured MTF curves agree with those of traditional bar pattern phantoms to within the limits of experimental uncertainty. An intercomparison of the Varian aS1000 and aS500-II detectors demonstrated an improvement in MTF for the aS1000 of 50–100% over the clinically relevant range 0.4–1 cycles/mm, yet with a corresponding reduction in CNR by a factor of p 2. Both detectors therefore offer advantages for different clinical applications. Characterisation of cone-beam CT (CBCT) facilities on two Varian On-Board Imaging (OBI) units revealed that only two out of six clinical modes had been calibrated by default, leading to errors of the order of 400 HU for some modes and materials – well outside the ±40 HU tolerance. Following calibration, all curves agreed sufficiently for dose calculation accuracy within 2%. CNR and MTF experiments demonstrated that a boost in MTF f50 of 20–30% is achievable by using a 5122 rather than a 3842 matrix, but with a reduction in CNR of the order of 30%. The MTF f50 of the single-pulse half-resolution radiographic mode of the Varian PaxScan 4030CB detector was measured in the plane of the detector as 1.0±0.1 cycles/mm using both a traditional tungsten edge and the new QEPI1 phantom. For digitally reconstructed radiographs (DRRs), a reduction in CT slice thickness resulted in an expected improvement in MTF in the patient scanning direction but a deterioration in the orthogonal direction, with the optimum slice thickness being 1–2 mm. Two general purposes display devices were calibrated against the DICOM Greyscale Standard Display Function (GSDF) to within the ±20% limit for Class 2 review devices. By providing an approach to image quality evaluation that is uniform across all radiotherapy imaging modalities this work enables consistent end-to-end optimisation of this fundamental part of the radiotherapy process, thereby supporting enhanced use of image-guidance at all relevant stages of radiotherapy and better supporting the clinical decisions based on it

Smart Wireless Sensor Networks

The recent development of communication and sensor technology results in the growth of a new attractive and challenging area - wireless sensor networks (WSNs). A wireless sensor network which consists of a large number of sensor nodes is deployed in environmental fields to serve various applications. Facilitated with the ability of wireless communication and intelligent computation, these nodes become smart sensors which do not only perceive ambient physical parameters but also be able to process information, cooperate with each other and self-organize into the network. These new features assist the sensor nodes as well as the network to operate more efficiently in terms of both data acquisition and energy consumption. Special purposes of the applications require design and operation of WSNs different from conventional networks such as the internet. The network design must take into account of the objectives of specific applications. The nature of deployed environment must be considered. The limited of sensor nodes� resources such as memory, computational ability, communication bandwidth and energy source are the challenges in network design. A smart wireless sensor network must be able to deal with these constraints as well as to guarantee the connectivity, coverage, reliability and security of network's operation for a maximized lifetime. This book discusses various aspects of designing such smart wireless sensor networks. Main topics includes: design methodologies, network protocols and algorithms, quality of service management, coverage optimization, time synchronization and security techniques for sensor networks