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Objective: The study's goal was to diagnose the condition at an earlier stage by employing the optimization-based technique for image segmentation to find deformities in MRI and Aura images Methods: Our methodology was based on tw...
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Objective: The study's goal was to diagnose the condition at an earlier stage by employing the optimization-based technique for image segmentation to find deformities in MRI and Aura images Methods: Our methodology was based on two case studies. The diseased data set of MRI images obtained from the UCI data set and Aura images from Bio-Well were taken into consideration. Using the Relevance Feedback Mechanism (RFM), the sick images that are most pertinent are determined. The optimization-based Cuckoo Search (CS) algorithm is used to find the best features. The resulting model utilising the Truncated Gaussian Mixture Model (TGMM) is used to compare the extracted characteristics. The most relevant images are chosen based on the likely hood estimation. Results: The suggested methodology is tested using 150 retrieved Aura images, 50 trained photos, and processing of the input image utilizing morphological techniques like dilation, erosion, opening, and closing to improve the image quality. Together with segmentation quality measurements including Global Consistency Error (GCE), Probability Random Index (PRI), and Volume of Symmetry(VOS), the results are assessed using image quality metrics such as Average Difference (AD), Maximum Difference (MD), and Image Fidelity (IF). Conclusion: The TGMM algorithm is used to conduct the experiment. The outcomes demonstrate the effectiveness of the suggested approaches in locating various injured tissues inside medical images obtained using MRI technology as well as in locating high-intensity energy zones in which a potential deformity is associated in Aura images. The outcomes reveal a respectable recognition accuracy of about 93%.
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Assessing quality of medical images is critical because the subsequent course of actions depend on it. Extensive use of clinical magnetic resonance (MR) imaging warrants a study in image indices used for MR images. The quality of ...
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Assessing quality of medical images is critical because the subsequent course of actions depend on it. Extensive use of clinical magnetic resonance (MR) imaging warrants a study in image indices used for MR images. The quality of MR images assumes particular significance in the determination of their reliability for diagnostics, response to therapies, synchronization across different imaging cycles, optimization of interventional imaging, and image restoration. In this paper, we review various techniques developed for the assessment of MR image quality. The reported quality indices can be broadly classified as subjective/objective, automatic/semi-automatic, region-of-interest/non-region-of-interest-based, full-reference/no-reference and HVS incorporated/non-HVS incorporated.The trade-off across the various indices lies in the computational complexity, assumptions, repeatability, and resemblance to human perception. Because images are eventually viewed by the human eye, it is found that it is important to incorporate aspects of human visual response, sensitivity, and characteristics in computing quality indices. Addition-ally, no-reference metrics are the most relevant due to the lack of availability of a golden standard against which images could be compared. Techniques that are objective and automatic are preferred for their repeatability and to eliminate avoidable errors due to factors like stress, which arise in human intervention.
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Shape is an important aspect of the spatial attributes of land-use segments in remotely sensed imagery, but it is still rarely used as a component in land-use classification or image-based land-use analysis. This study aimed to qu...
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Shape is an important aspect of the spatial attributes of land-use segments in remotely sensed imagery, but it is still rarely used as a component in land-use classification or image-based land-use analysis. This study aimed to quantitatively characterize land-use classes using shape metrics. The study was conducted in a case area located in southern China, covering 12 scenes of SPOT-5 images. There were a total of 10 metrics selected for the analysis: convexity (CONV), solidity (SOLI), elongation (ELONG), roundness (ROUND), rectangular fitting (RECT), compactness (COMP), form factor (FORM), square pixel metric (SqP), fractal dimension (FD), and shape index (SI). The last five metrics were used to measure the complexity of shape. Six land-use classes were investigated in the case area: roads; cultivated lands; settlements; rivers; ponds; and forest and grass lands. The results showed that all the typical shape properties of the land-use segments can be well measured by shape metrics. We identified the land-use classes whose values were significantly differentiated from the other classes for each metric. Finally, we selected five shape metrics (SOLI, ELONG, ROUND, RECT, FORM) by visual comparison and statistical analysis of the metrics values, and deduced the "shape metric signatures" (SMS) of the different land-use classes. SMS were found to be accurate and predictive discriminators of land-use classes within the study area. Our results showed that SMS can clearly distinguish spectrally similar land-use classes. The results of this study will help to build a more accurate and intelligent object-oriented classification system for land-use classes.
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The quality of an image produced by the Whole Slide Imaging (WSI) scanners is of critical importance for using the image in clinical diagnosis. Therefore, it is very important to monitor and ensure the quality of images. Since sub...
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The quality of an image produced by the Whole Slide Imaging (WSI) scanners is of critical importance for using the image in clinical diagnosis. Therefore, it is very important to monitor and ensure the quality of images. Since subjective image quality assessments by pathologists are very time-consuming, expensive and difficult to reproduce, we propose a method for objective assessment based on clinically relevant and perceptual image parameters: sharpness, contrast, brightness, uniform illumination and color separation; derived from a survey of pathologists. We developed techniques to quantify the parameters based on content-dependent absolute pixel performance and to manipulate the parameters in a predefined range resulting in images with content-independent relative quality measures. The method does not require a prior reference model. A subjective assessment of the image quality is performed involving 69 pathologists and 372 images (including 12 optimal quality images and their distorted versions per parameter at 6 different levels). To address the inter-reader variability, a representative rating is determined as a one-tailed 95% confidence interval of the mean rating. The results of the subjective assessment support the validity of the proposed objective image quality assessment method to model the readers’ perception of image quality. The subjective assessment also provides thresholds for determining the acceptable level of objective quality per parameter. The images for both the subjective and objective quality assessment are based on the HercepTestTM slides scanned by the Philips Ultra Fast Scanners, developed at Philips Digital Pathology Solutions. However, the method is applicable also to other types of slides and scanners.
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The fused image derived from multimodality, multi-focus, multi-view and multidimensional, for real world applications in the field of medical imaging, remote sensing, satellite imaging, machine vision etc., are gaining much attent...
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The fused image derived from multimodality, multi-focus, multi-view and multidimensional, for real world applications in the field of medical imaging, remote sensing, satellite imaging, machine vision etc., are gaining much attention in the recent research. Therefore, it is important to validate the fused image in different perspectives such as information, edge, structure, noise and contrast for quality analysis. From this aspect, the information of fused image should be better than the source images without loss of information and false information. This survey is focused on analyzing the various quantitative metrics that are used in the literature to measure the enhanced information of fused image when it is compared to the source/reference images. The objective of this study is to group or classify the metrics under different categories such as information, noise, error, correlation and structural similarity measures for discussion and analysis. In reality, the calculated metric values are useful in determining the suitable fusion technique of the particular dataset with its required perspective as an outcome of the fusion process.
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In this paper we present new examples of fuzzy metrics in the sense of George and Veeramani. The examples have been classified attending to their construction and most of the well-known fuzzy metrics are particular cases of those ...
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In this paper we present new examples of fuzzy metrics in the sense of George and Veeramani. The examples have been classified attending to their construction and most of the well-known fuzzy metrics are particular cases of those given here. In particular, novel fuzzy metrics, by means of fuzzy and classical metrics and certain special types of functions, are introduced. We also give an extension theorem for two fuzzy metrics that agree in its nonempty intersection. Finally, we give an application of this type of fuzzy metrics to color image processing. We propose a fuzzy metric that simultaneously takes into account two different distance criteria between color image pixels and we use this fuzzy metric to filter noisy images, obtaining promising results. This application is also illustrative of how fuzzy metrics can be used in other engineering problems.
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A novel objective non-reference metric for multimodal image sensor fusion is presented. Using the joint segmentation of the input images and entropy of the regions as the priority, an 'ideal' fused image is obtained. The metric is...
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A novel objective non-reference metric for multimodal image sensor fusion is presented. Using the joint segmentation of the input images and entropy of the regions as the priority, an 'ideal' fused image is obtained. The metric is based on computing how accurately the important regions from the input images are transferred into the fused image. Experiments have shown that the obtained metric values correspond better to the subjective quality of the fused images than other state-of-the-art fusion metrics.
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Let M = {v_1, v_2 ... v_n} be an ordered set of vertices in a graph G. Then (d(u,v_1),d(u,v_2)...d(u,v_n)) is called the M-coordinates of a vertex u of G. The set M is called a metric basis if the vertices of G have distinct M-coo...
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Let M = {v_1, v_2 ... v_n} be an ordered set of vertices in a graph G. Then (d(u,v_1),d(u,v_2)...d(u,v_n)) is called the M-coordinates of a vertex u of G. The set M is called a metric basis if the vertices of G have distinct M-coordinates. A minimum metric basis is a set M with minimum cardinality. The cardinality of a minimum metric basis of G is called minimum metric dimension. This concept has wide applications in motion planning and in the field of robotics. In this paper we provide bounds for minimum metric dimension of certain class of enhanced hypercube networks
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We present low-frequency (80 – 240 MHz) radio observations of circular polarization in 16 isolated type III solar radio bursts using the MurchisonWidefield Array (MWA) between August 2014 and November 2015. For most of the bursts...
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We present low-frequency (80 – 240 MHz) radio observations of circular polarization in 16 isolated type III solar radio bursts using the MurchisonWidefield Array (MWA) between August 2014 and November 2015. For most of the bursts, near burst onset, we find on average 9% circular polarization at 80 MHz and 22% at 240 MHz whereas these percentages are 5% and 20% near burst maximum. The polarization fractions are neither constant in time nor uniform over the spatial extents of the bursts. We measure polarization fractions as a function of burst source's position. On average, near both burst onset and maximum, we find higher polarization near the disk center and lower polarization when the burst source is near the limb. We study total intensity (Stokes I ), circularly polarized intensity (Stokes V ), and polarization fraction (|V |/I ) profiles for type III bursts with and without source motion as a function of position at times when the intensity of bursts is maximum. For the burst event with no source motion, we find symmetric profiles for Stokes I , V , and |V |/I. We find symmetric I and V but asymmetric |V |/I profiles for burst events which have source motion. We argue that this is due to the fundamental emission at the front of a type III electron beam and motion of the burst source. We then perform spectropolarimetric imaging studies of moving burst sources and analyze their motion. At burst onset, we obtain relatively higher polarization fractions, which is considered to be due to a large contribution from fundamental plasma emission at the front of the beam. At burst maximum, the polarization fraction is lower due to the combination of fundamental and harmonic components. After peak intensity, the emission is dominated again by the fundamental component that decays until the end of a burst with lesser polarization fraction than earlier. We argue that the fundamental radiation that decays over time after peak burst intensity is strongly scattered. This pattern
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