3,069 research outputs found

    Hardware acceleration using FPGAs for adaptive radiotherapy

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    Adaptive radiotherapy (ART) seeks to improve the accuracy of radiotherapy by adapting the treatment based on up-to-date images of the patient's anatomy captured at the time of treatment delivery. The amount of image data, combined with the clinical time requirements for ART, necessitates automatic image analysis to adapt the treatment plan. Currently, the computational effort of the image processing and plan adaptation means they cannot be completed in a clinically acceptable timeframe. This thesis aims to investigate the use of hardware acceleration on Field Programmable Gate Arrays (FPGAs) to accelerate algorithms for segmenting bony anatomy in Computed Tomography (CT) scans, to reduce the plan adaptation time for ART. An assessment was made of the overhead incurred by transferring image data to an FPGA-based hardware accelerator using the industry-standard DICOM protocol over an Ethernet connection. The rate was found to be likely to limit the performanceof hardware accelerators for ART, highlighting the need for an alternative method of integrating hardware accelerators with existing radiotherapy equipment. A clinically-validated segmentation algorithm was adapted for implementation in hardware. This was shown to process three-dimensional CT images up to 13.81 times faster than the original software implementation. The segmentations produced by the two implementations showed strong agreement. Modifications to the hardware implementation were proposed for segmenting fourdimensional CT scans. This was shown to process image volumes 14.96 times faster than the original software implementation, and the segmentations produced by the two implementations showed strong agreement in most cases.A second, novel, method for segmenting four-dimensional CT data was also proposed. The hardware implementation executed 1.95 times faster than the software implementation. However, the algorithm was found to be unsuitable for the global segmentation task examined here, although it may be suitable as a refining segmentation in the context of a larger ART algorithm.Adaptive radiotherapy (ART) seeks to improve the accuracy of radiotherapy by adapting the treatment based on up-to-date images of the patient's anatomy captured at the time of treatment delivery. The amount of image data, combined with the clinical time requirements for ART, necessitates automatic image analysis to adapt the treatment plan. Currently, the computational effort of the image processing and plan adaptation means they cannot be completed in a clinically acceptable timeframe. This thesis aims to investigate the use of hardware acceleration on Field Programmable Gate Arrays (FPGAs) to accelerate algorithms for segmenting bony anatomy in Computed Tomography (CT) scans, to reduce the plan adaptation time for ART. An assessment was made of the overhead incurred by transferring image data to an FPGA-based hardware accelerator using the industry-standard DICOM protocol over an Ethernet connection. The rate was found to be likely to limit the performanceof hardware accelerators for ART, highlighting the need for an alternative method of integrating hardware accelerators with existing radiotherapy equipment. A clinically-validated segmentation algorithm was adapted for implementation in hardware. This was shown to process three-dimensional CT images up to 13.81 times faster than the original software implementation. The segmentations produced by the two implementations showed strong agreement. Modifications to the hardware implementation were proposed for segmenting fourdimensional CT scans. This was shown to process image volumes 14.96 times faster than the original software implementation, and the segmentations produced by the two implementations showed strong agreement in most cases.A second, novel, method for segmenting four-dimensional CT data was also proposed. The hardware implementation executed 1.95 times faster than the software implementation. However, the algorithm was found to be unsuitable for the global segmentation task examined here, although it may be suitable as a refining segmentation in the context of a larger ART algorithm

    On the Assouad dimension of self-similar sets with overlaps

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    It is known that, unlike the Hausdorff dimension, the Assouad dimension of a self-similar set can exceed the similarity dimension if there are overlaps in the construction. Our main result is the following precise dichotomy for self-similar sets in the line: either the \emph{weak separation property} is satisfied, in which case the Hausdorff and Assouad dimensions coincide; or the \emph{weak separation property} is not satisfied, in which case the Assouad dimension is maximal (equal to one). In the first case we prove that the self-similar set is Ahlfors regular, and in the second case we use the fact that if the \emph{weak separation property} is not satisfied, one can approximate the identity arbitrarily well in the group generated by the similarity mappings, and this allows us to build a \emph{weak tangent} that contains an interval. We also obtain results in higher dimensions and provide illustrative examples showing that the `equality/maximal' dichotomy does not extend to this setting.Comment: 24 pages, 2 figure

    Improving research and policy interactions requires a better understanding of what works in different contexts.

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    There is keen interest in many jurisdictions in finding ways to improve the way that research evidence informs policy. One possible mechanism for this is to embed academics within government agencies either as advisers or full staff members. Our commentary argues that, in addition to considering the role of academics in government as proposed by Glied and colleagues, we need to understand better how research and policy interactions function across policy sectors. We believe more comparative research is needed to understand if and why academics from certain disciplines are more likely to be recruited to work in some policy sectors rather than others. We caution against treating government as monolithic by advocating the same model for collaborative interaction between academics and government. Lastly, we contend that contextualized research is needed to illuminate important drivers of research and policy interactions before we can recommend what is likely to be more and less effective in different policy sectors

    The internationalization of the Brazilian Public Prosecutor's Office : anti-corruption and corporate investments in the 2000s

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    The success of different categories of legal professionals in building positions of state power in Brazil since the end of the military regime is in line with the legitimation of models of law and international cooperation. This article focuses on the connections between Brazilian legal actors and the international ‘fight against corruption’. By looking at the international connections of Brazil’s Public Prosecutor’s Office (MPF), we aim to show how the promotion of anti-corruption models of law is the result of corporate cooperation strategies. We cite as evidence overseas travel by MPF agents and their connections with the international field in recent decades. We start by analyzing cooperation documents and then attempt to trace the MPF’s pathway towards internationalization during the 2000s

    Hardware accelerated image processing to enable real-time adaptive radiotherapy

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    The accuracy of radiotherapy is constrained by organ motion and deformation occurring between the acquisition of CT and MR images used to plan the treatment and the time at which the treatment is delivered. Adaptive radiotherapy uses image data acquired at the time of treatment to adapt the original treatment plan to match the current patient anatomy. Currently, the image processing and dose calculation algorithms required to perform this plan adaptation cannot be executed in a clinically acceptable timeframe. Hardware acceleration has the potential to speedup these algorithms, making real-time adaptive radiotherapy a clinical possibility[1]. Hardware acceleration is a technique where an algorithm is implemented using hardware that is better suited to the specific algorithm than more general purpose processors in order to reduce the execution time of the algorithm. This can be achieved using field programmable gate arrays (FPGA), which are devices consisting of reconfigurable hardware, allowing their function to be customised for a specific application. These devices have been shown to be able to accelerate image processing algorithms pertinent to adaptive radiotherapy[2]. In this study a global thresholding algorithm based on Otsu’s method combined with a three dimensional mean filter was used to segment a series of CT images of a Modus QUASAR respiratory motion phantom into three unique classes. A Xilinx Zynq Z-7020 device consisting of a dual-core ARM Cortex-A9 central processing unit (CPU) coupled to an 85 000 logic cell FPGA was used to accelerate the algorithm by implementing sections of it in the reconfigurable hardware. The execution time of this implementation was compared to an implementation running on an ARM CPU and Intel Core-i5 CPU. The execution times of the implementations are shown in table 1. The hardware accelerated implementation was found to execute nearly sixty times as fast as the un-accelerated algorithm. The hardware accelerated implementation was also found to run around 14% faster than on the more powerful Intel Core-i5 CPU. Figure 1 shows an example of the segmentation results where the blue contour represents the boundary between two of the classes. In the algorithms presented here the overhead of transferring data to the hardware represents a significant proportion of the algorithm execution time. It is anticipated that greater acceleration will be possible for algorithms with greater computational complexity because the data transfer overhead will represent a smaller proportion of the overall execution time. The requirement for fast processing in radiotherapy is likely to increase as the amount of data available to more accurately guide treatment increases through the use of techniques such as 4D CT and image-guided radiotherapy. FPGA have been shown to be effective at accelerating certain algorithms required for real-time adaptive radiotherapy, however, more research is required to establish which will execute faster on other types of hardware, such as CPU and graphical processing units (GPU). It is likely that heterogeneous computing platforms, composed of a mixture of hardware architectures, will be used in the future implementation of real-time adaptive radiotherapy. References: 1.K. Østergaard Noe, B.D. De Senneville, U.V. Elstrøm, K. Tanderup, T.S. Sørensen, “Acceleration and validation of optical flow based deformable registration for image-guided radiotherapy,” Acta Oncologica, vol. 47, no. 7, pp.1286-1293, 2008 2.O. Dandekar, R. Shekhar, “FPGA-Accelerated Deformable Image Registration for Improved Target-Delineation During CT-Guided Interventions,” IEEE Trans. Biomed. Circuits Syst., vol. 1, no. 2, pp.116-127, 200

    The Urban Political Ecology of Post-industrial Scottish Towns: Examining Greengairs and Ravenscraig

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    Urban ecological politics is shaped by both moments of concerted action and more silent perceptions and responses. Instead of only being evident in situations of organised protest, the politics of urban ecology is also manifested, in material and symbolic terms, in the daily life of the residents. The fragmentation of urban political ecology turns out to be an important element in the affirmation of post-political forms of urban governance. Those issues were the object of fieldwork research carried out in Greengairs and Ravenscraig, two towns in North Lanarkshire, near Glasgow, with the goal of unravelling the understanding and the coping mechanisms of environmentally deprived residents. The towns are permeated by a widespread, often dissimulated, political ecology that is nonetheless always present. Empirical results demonstrate that a more comprehensive handling of the political ecology of the urban is crucial in order to halt the sources of marginalisation and ecological degradation

    High-level synthesis for medical image processing on Systems on Chip : a case study

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    Adaptive radiotherapy is a technique intended to increase the accuracy of radiotherapy. Currently, it is not clinically feasible due to the time required to process the images of patient anatomy. Hardware acceleration of image processing algorithms may allow them to be carried out in a clinically acceptable timeframe. This paper presents the experiences encountered using high-level synthesis tools to design an accelerated segmentation algorithm for computed tomography images targeted for implementation on a System on Chip. Hardware coprocessors and their interfaces for optimal threshold generation and 3D mean filter algorithms were synthesised from C++ functions. Hardware acceleration significantly outperformed the software only implementation. The high-level synthesis tools allowed the rapid exploration of different design options. However, hardware design knowledge was still necessary in order to interpret the results effectively
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