We present an algorithm for creating high resolution anatomically plausible images consistent with acquired clinical brain MRI scans with large inter-slice spacing. Although large databases of clinical images contain ...
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ISBN:
(数字)9783319590509
ISBN:
(纸本)9783319590509;9783319590493
We present an algorithm for creating high resolution anatomically plausible images consistent with acquired clinical brain MRI scans with large inter-slice spacing. Although large databases of clinical images contain a wealth of information, medical acquisition constraints result in sparse scans that miss much of the anatomy. These characteristics often render computational analysis impractical as standard processingalgorithms tend to fail when applied to such images. Highly specialized or application-specific algorithms that explicitly handle sparse slice spacing do not generalize well across problem domains. In contrast, our goal is to enable application of existing algorithms that were originally developed for high resolution research scans to significantly undersampled scans. We introduce a model that captures fine-scale anatomical similarity across subjects in clinical image collections and use it to fill in the missing data in scans with large slice spacing. Our experimental results demonstrate that the proposed method outperforms current upsampling methods and promises to facilitate subsequent analysis not previously possible with scans of this quality.
Network traffic identification plays a major role in modern-day network monitoring systems. Most network systems identify traffic based on features such as, flow statistics, static signatures and port numbers. Identif...
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ISBN:
(纸本)9781538675199
Network traffic identification plays a major role in modern-day network monitoring systems. Most network systems identify traffic based on features such as, flow statistics, static signatures and port numbers. Identifying network traffic is essential, because plenty of information regarding a network flow can be learned by knowing the application protocol associated with it. However, the challenge for traffic classification is to identify features in the network flow data. This paper explores the issue of network traffic identification with neural network and deep learning. A convolutional neural network (CNN) with different optimization algorithms is trained to identify application protocols based on network flow data. The image and text processing hypothesis of the CNN model is extended to naturally fit to the curated dataset. Protocol labels with a high frequency distribution are easily detected by the model, and the results show that the CNN model works equally well on network flow data. A discussion on the performance of different optimization algorithms used with the CNN model is presented.
Mathematical science in tight integration with the natural and life sciences provide sophisticated models and algorithms of knowledge acquisition. Overall rapid development of nowadays science and technologies is a di...
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Mathematical science in tight integration with the natural and life sciences provide sophisticated models and algorithms of knowledge acquisition. Overall rapid development of nowadays science and technologies is a direct consequence of such interdisciplinary developments. The same time, there exist particular research domains, e.g., the biological research domain, that appears as a semi-exact discipline (except of its genomics part). This is due to insufficient level of readiness of mathematical, physical and chemical sciences, being in power to provide the proper interpretation of the real size biological interrelations. Enrichment of mathematics to this new sophisticated level may be a long lasting but unavoidable process. Current series of studies is driven by a number of applied problems that are focused around the unique integrative technique of getting knowledge from fragmented data and descriptions. A large number of links connect these ideas to the problems of: artificial intelligence, intelligent information management, high performance computation, and other research domains. Our objective is in provision of integrated solutions of inverse type combinatorial problems that will help to sustain a set of applied problems. The base set of applied problems we consider involves the radiation therapy planning, the wireless sensor network integrated-connectivity-coverage protocols with its decentralized management, and the network tomography scenario devoted to the issue of energy minimization in networks. As we will see the necessary mathematical technique of solving these problems is focused around the model description by the sets of constraints and relations, by integration of the partial knowledge about these models. Two scenarios have been considered. One is based on the use of projections and their interpretation, and the second is based on the local neighbourhood analysis (generic projections). Given projections and/or neighbourhoods (in inverse manner),
During last years, images and videos have become widely used in many daily applications. Indeed, they can come from cameras, smartphones, social networks of from medical devices. Generally, these images and videos are...
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ISBN:
(纸本)9781450352819
During last years, images and videos have become widely used in many daily applications. Indeed, they can come from cameras, smartphones, social networks of from medical devices. Generally, these images and videos are used for illustrating people or objects (cars, trains, planes, etc.) in many situations such as airports, train stations, public areas, sport events, hospitals, etc. Thus, image and video processingalgorithms have got increasing importance, they are required from various computer visions applications such as motion tracking, real time event detection, database (images and videos) indexation and medical computer aided diagnosis methods. In this paper, we propose a cloud platform that integrates the above-mentioned methods, which are generally developed with popular open source image and video processing libraries (OpenCv(1), OpenGL(2), ITK3, vTK4, etc.). Theses modules are automatically integrated and configured in the cloud application. Thus, the platform users will have access to different computer vision techniques without the need to download, install and configure the corresponding software. Each guest can select the required application, load its data and get the output results in a safe and simple way. The cloud platform can handle the variety of Operating systems and programming languages (C++, Java, Python, etc.). Experimentations were conducted within two kinds of applications. The first represents medical methods such as image segmentation in MR images, 3D image reconstruction from 2D radiographs, left ventricle segmentation and tracking from 2D echocardiography. The second kind of applications is related to video processing such as face, people and cars tracking, and abnormal event detection in crowd videos.
Synthetic aperture radar (SAR) is a widely used technique suited for real-time and all-weather imaging of natural surfaces and artificial objects. To improve image resolution and increase accuracy of estimation parame...
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ISBN:
(纸本)9781509062690
Synthetic aperture radar (SAR) is a widely used technique suited for real-time and all-weather imaging of natural surfaces and artificial objects. To improve image resolution and increase accuracy of estimation parameters the problem of statistical synthesis of signal processing algorithm in SAR is solved. Proposed method allows to form images with super-resolution in azimuth and range. Synthesis is performed using modern theory of radio engineering systems statistical optimization.
In the last decade Ground-Based SAR (GB-SAR) technology has been demonstrated to be one of the most efficient tool for slope monitoring in open pit mines scenarios. However, especially for open pit mines application, ...
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In the last decade Ground-Based SAR (GB-SAR) technology has been demonstrated to be one of the most efficient tool for slope monitoring in open pit mines scenarios. However, especially for open pit mines application, one of the relevant limits is the azimuth coverage, being the mine often of elliptical shape. In this context, the IBIS-FM product of IDS GeoRadar company can reach about 80° of horizontal coverage, and can be overcome by IBIS-Rover product that can reach 270° of horizontal coverage but increasing the acquisition time. The recent IBIS-ArcSAR product developed by IDS GeoRadar can overcome these limits, offering a full 360° of horizontal coverage in less than 1 minute of acquisition time, with additional feature of a constant angular resolution. Moreover, by exploiting the new capability of MIMO (Multiple Input Multiple Output) Radar channels, the vertical height or Digital Elevation Model (DEM) of the mine can be reconstructed through simple and computationally fast interferometric processingalgorithms, together with an enhanced focusing of 2D SAR image that is an open issue in Arc-scanning SAR systems.
Corner detection is an important task in digital imageprocessing. Corner detec- tion algorithms are widely used in pattern recognition, image mosaicing, motion detection, etc. The implementations of such algorithm in...
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Corner detection is an important task in digital imageprocessing. Corner detec- tion algorithms are widely used in pattern recognition, image mosaicing, motion detection, etc. The implementations of such algorithm in software/hardware can be challenging. One classical algorithm for finding corners in images is proposed by Harris and Stephens in 1988, commonly known as Harris corner detection al- gorithm; There have been different implementations of the algorithm in OpenCv and on FPGA. The implementations of the algorithm in hardware have been rela- tively less, and most importantly the architectures of the algorithm on FPGA have relatively been unexplored. LIDE, created at University of Maryland, College Park, is a light-weight dataflow environment for rapid prototyping of DSP systems using dataflow techniques. The framework in C programming language is called LIDE-C, in verilog HDL is called LIDE-v. This light-weight framework makes modeling of DSPs easy in both software and hardware. It is platform- and language-agnostic. This thesis work models the application both in LIDE-C and LIDE-v, our emphasis is, however, to propose multi- architecture corner detection Harris algorithm in LIDE-v. In LIDE, computations are distributed to different computation nodes in dataflow graphs. Each node is called actor in LIDE, and each actor has different modes of computation. Depending on how we construct a dataflow graph for an application and how we design actors of a dataflow graph, we easily create different implementations for the same algorithm. In this thesis, different hardware architecture of the Harris algorithm will be pro- posed with different latency, resource usage, and throughput characteristics. Our preliminary results reveal, among other things, that unfolding for the non-max sup- pression actor not only improve performance but also decrease resource usage.
For the first time experimentally investigated the use of a vision system using the technology of depth maps, infrared depth sensor, laser rangefinder, lidar to determine the relief and geometric dimensions of the obj...
For the first time experimentally investigated the use of a vision system using the technology of depth maps, infrared depth sensor, laser rangefinder, lidar to determine the relief and geometric dimensions of the object on digital stereo images, which allows continuous monitoring of the state of any process. Methods of digital imageprocessing are presented. The main advantages of such systems are considered.
In this paper we study ability to sparse the neural networks which are used in the task of person re-identification in multicamera CCTvsystems. Sparse neural network allows significant reducing of the computation com...
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This paper introduces conjugate gradient algorithms for training quaternion-valued feedforward neural networks. Because these algorithms had better performance than the gradient descent algorithm in the real- and comp...
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