Digital images and digital imageprocessing facilitated significant progress in numerous areas where medicine is an important one of them. Computer-aided detection and diagnostics systems are used to assist specialist...
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ISBN:
(纸本)9788086943503
Digital images and digital imageprocessing facilitated significant progress in numerous areas where medicine is an important one of them. Computer-aided detection and diagnostics systems are used to assist specialists in interpretation of medical digital images. One of the important research issues is detection and classification of the chronic obstructive pulmonary disease in lung CT images In this paper we proposed a method for emphysema classification based on texture and intensity features. Only six different characteristics of the uniform local binary pattern and intensity histogram were used as input vector for support vector machine that was used as classifier. Feature vector was significantly reduced compared to the other state-of-the-art methods while the classification accuracy was increased. On images from standard dataset global accuracy of our proposed algorithm was 98.18% compared to 95.24% and 93.9% of two other compared algorithms.
images can now be easily modified due to advances in digital imageprocessing. image forgery is the process of manipulating or changing a digital image in order to conceal vital information. Nowadays, as technology ad...
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A technique to perform full spectral based color calculations through an extension of OpenGL has been created. This method of color computations is more accurate than the standard RGB model that most computer graphics...
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A technique to perform full spectral based color calculations through an extension of OpenGL has been created. This method of color computations is more accurate than the standard RGB model that most computer graphics algorithms utilize. By maintaining full wavelength information in color calculations, it is also possible to interactively simulate and display many important color phenomena such as metamerism and fluorescence. This technique is not limited to creating simple images suitable for interactive display, however. Using this extension, it is also possible to synthesize spectroradiometric images of arbitrary spatial and spectral resolution, for use in color imaging system analysis.
Computer Aided Diagnosis (CAD) has changed the way of medical diagnostics. As similar to other walk of diagnostics field, CAD is having high potential in breast cancer prognosis because of its highest accuracy. CAD ma...
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ISBN:
(纸本)9781479949397
Computer Aided Diagnosis (CAD) has changed the way of medical diagnostics. As similar to other walk of diagnostics field, CAD is having high potential in breast cancer prognosis because of its highest accuracy. CAD may play a very important role in developing countries i.e. EIT-MEM (Electrical Impedance Tomography Multi-frequency Electrical Impedance Mammography) device being used for breast cancer defection. MEM-EIT produces tomography based mammograms which are considered most reliable method of early detection of breast cancer. Cancer diagnostic expert all over the world find this non-invasive technique very accurate as it is one dimensional representation of images in terms of temperature however the accuracy is limited and investigator fail to take into account the spatial co-ordination between the pixels which is crucial in cancerous tumour detection and their classification (cancerous or normal) in FIT (Electrical Impedance Tomography) - based mammogram images. In this study, we are trying to focus an algorithms based CAD (Computer Aided Diagnosis) model for tumour detection and classification. We model it by ARIMA model (autoregressive integrated moving average (ARIMA) model) and parameter estimation will be performed using leas-square method. Our system classifies the tumour into three categories- (i) healthy tissue (ii) benign tissue (iii) cancerous tissue along with above three segments the performance analysis between 2D image and ID image will be done for better accuracy and sensitivity detection.
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:
(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.
Computational ghost imaging(CGI), utilizing a single-pixel detector, has been extensively used in many fields. However, in order to achieve a high-quality reconstructed image, a large number of iterations are needed, ...
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ISBN:
(数字)9781510617520
ISBN:
(纸本)9781510617520;9781510617513
Computational ghost imaging(CGI), utilizing a single-pixel detector, has been extensively used in many fields. However, in order to achieve a high-quality reconstructed image, a large number of iterations are needed, which limits the flexibility of using CGI in practical situations, especially in the field of object recognition. In this paper, we purpose a method utilizing the feature matching to identify the number objects. In the given system, approximately 90% of accuracy of recognition rates can be achieved, which provides a new idea for the application of single pixel imaging in the field of object recognition
Each and every color imaging device should be custom calibrated both to enhance imageprocessingalgorithms and to produce pleasing and faithful images of the captured scenes or medias. Custom calibrations, however, a...
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Each and every color imaging device should be custom calibrated both to enhance imageprocessingalgorithms and to produce pleasing and faithful images of the captured scenes or medias. Custom calibrations, however, are usually not performed because calibration instruments are either too slow to be used on the manufacturing line or the instruments lack the necessary accuracy. We have developed a calibration instrument that enables both fast and accurate imager calibrations. The instrument is based on emissive narrow-band light sources - light emitting diodes - arranged in a grid pattern or chart configuration. We refer to the instrument as the emissive calibration chart or the EC chart. We compare the emissive calibration chart to other calibration instruments, which include reflective charts, like the Macbeth ColorChecker or DC charts, and monochromators. The results demonstrate that custom calibrations of each and every imager could be accurately determined on the manufacturing line using the emissive calibration chart.
Calibration is a well-studied property of predictors which guarantees meaningful uncertainty estimates. Multicalibration is a related notion - originating in algorithmic fairness - which requires predictors to be simu...
Aerial image simulation is a fundamental problem in advanced lithography for chip fabrication. Since it requires a huge number of mathematical computations, an efficient yet accurate implementation becomes a necessity...
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ISBN:
(纸本)9781479910717
Aerial image simulation is a fundamental problem in advanced lithography for chip fabrication. Since it requires a huge number of mathematical computations, an efficient yet accurate implementation becomes a necessity. In the literature, GPU or FPGA has demonstrated its potential for accelerating aerial image simulation. However, the comparisons of GPU or FPGA to CPU were not done thoroughly. In particular, careful tunings for the CPU-based method were missing in the previous works, while the recent CPU architectures have significant modifications toward high performance computing capabilities. In this paper, we present and discuss several algorithms for the aerial image simulation on multi-core SIMD CPU. Our fastest method achieves up to 73X speedup over the baseline serial approach and outperforms the state-of-the-art GPU-based approach by up to 2X speedup on a single hex-core SIMD CPU. We show that the performance on the multi-core SIMD CPU is promising, and that careful CPU tunings are necessary in order to exploit its computing capabilities.
The stable closure of the gate affects the safety performance and normal operation of the gate, and it is necessary to detect the gap distance of the closed door, but the direct observation of the gate monitoring imag...
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