The safety and serviceability of civil infrastructures have to be ensured either as part of a periodic inspection program or immediately following a given hazardous event. The use of digital imaging techniques to iden...
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The safety and serviceability of civil infrastructures have to be ensured either as part of a periodic inspection program or immediately following a given hazardous event. The use of digital imaging techniques to identify the deformed or deteriorated surfaces of structures is a substantial area of research and aims to investigate a number of unknown parameters, including damage quantification and condition rating. This manuscript illustrates the integration of previously developed fuzzy logic-based decision-making tools with the currently developed image processing algorithm to quantify the damage for the condition rating of civil infrastructures. The proposed integrated framework exploits visual specifics of different elements of the infrastructure to perform automated evaluation of structural anomalies such as cracks and surface degradation. Two different image segmentation tools, (1)bottom hat transform and (2)hue, saturation, color (HSV) thresholding, are applied to identify the surface defects. The developed image processing software is used with the fuzzy set framework proposed in the previous research to gauge the damage indices due to various deterioration types like corrosion, alkali aggregate reaction, freeze-thaw attack, sulfate attack, acid attack or loading, fatigue, shrinkage, and honeycombing. Case studies of a long-span bridge and a warehouse building are illustrated for concept validation. The refined comprehensive method is presented as a graphical user interface (GUI) to facilitate the real-time condition assessment of civil infrastructures. (c) 2018 American Society of Civil Engineers.
We aim to study the set of color sets of continuous regions of an image given as a matrix of m rows over n >= m columns where each element in the matrix is an integer from [1, sigma] named a color. The set of disti...
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We aim to study the set of color sets of continuous regions of an image given as a matrix of m rows over n >= m columns where each element in the matrix is an integer from [1, sigma] named a color. The set of distinct colors in a region is called fingerprint. We aim to compute, index and query the fingerprints of all rectangular regions named rectangles. The set of all such fingerprints is denoted by F. A rectangle is maximal if it is not contained in a greater rectangle with the same fingerprint. The set of all locations of maximal rectangles is denoted by L. We first explain how to determine all the vertical bar L vertical bar maximal locations with their fingerprints in expected time O (nm(2)sigma) using a Monte Carlo algorithm (with polynomially small probability of error) or within deterministic O (nm(2)sigma log(vertical bar L vertical bar/nm(2) + 2)) time. We then show how to build a data structure which occupies O(nm logn + vertical bar L vertical bar) space such that a query which asks for all the maximal locations with a given fingerprint f can be answered in time O(vertical bar f vertical bar + log logn + k), where k is the number of maximal locations with fingerprint f. If the query asks only for the presence of the fingerprint, then the space usage becomes O (nm logn + vertical bar F vertical bar) while the query time becomes O(nm log logn + vertical bar F vertical bar). We eventually consider the special case of squared regions (squares). (C) 2016 Elsevier B.V. All rights reserved.
A semi-automated imaging system is described to quantitate estrogen and progesterone receptor immunoreactivity in human breast cancer. The system works for any conventional method of image acquisition using microscopi...
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A semi-automated imaging system is described to quantitate estrogen and progesterone receptor immunoreactivity in human breast cancer. The system works for any conventional method of image acquisition using microscopic slides that have been processed for immunohistochemical analysis of the estrogen receptor and progesterone receptor. Estrogen receptor and progesterone receptor immunohistochemical staining produce colorimetric differences in nuclear staining that conventionally have been interpreted manually by pathologists and expressed as percentage of positive tumoral nuclei. The estrogen receptor and progesterone receptor status of human breast cancer represent important prognostic and predictive markers of human breast cancer that dictate therapeutic decisions but their subjective interpretation result in interobserver, intraobserver and fatigue variability. Subjective measurements are traditionally limited to a determination of percentage of tumoral nuclei that show positive immunoreactivity. To address these limitations, imaging algorithms utilizing both colorimetric (RGB) as well as intensity (gray scale) determinations were used to analyze pixels of the acquired image. image acquisition utilized either scanner or microscope with attached digital or analogue camera capable of producing images with a resolution of 20 pixels /10 mu. Areas of each image were screened and the area of interest richest in tumour cells manually selected for image processing. images were processed initially by JPG conversion of SVS scanned virtual slides or direct JPG photomicrograph capture. Following image acquisition, images were screened for quality, enhanced and processed. The algorithm-based values for estrogen receptor and progesterone receptor percentage nuclear positivity both strongly correlated with the subjective measurements (intraclass correlation: 0.77;95% confidence interval: 0.59, 0.95) yet exhibited no interobserver, intraobserver or fatigue variability. In addition
Background: immunocytochemical methods for quantitating Her-2/neu immunoreactivity rest on subjective semi-quantitative interpretations with resulting interobserver, intraobserver, and fatigue variability. Methods: To...
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Background: immunocytochemical methods for quantitating Her-2/neu immunoreactivity rest on subjective semi-quantitative interpretations with resulting interobserver, intraobserver, and fatigue variability. Methods: To standardize and quantitate measurements of Her-2/neu immunoreactivity, we created epithelial-recognition and specific membrane-recognition algorithms, which could image breast cancer cells against a background of stroma, compartmentalize the cancer cell into nucleus, cytoplasm and membrane, and quantitate the degree of Her-2/neu membrane immunoreactivity based on both gray scale intensity and RGB colorimetric determinations. image acquisition utilized either scanner or microscope with attached camera with a resolution of 20 pixels/10 mu m. Areas of 150 whole slides were screened and the regions of interest manually selected for image processing. Three hundred TMA cores were directly processed. images were acquired by jpg conversion of svs virtual slides or direct jpg photomicrograph capture. images were then assessed for quality and processed. Results: The digital algorithms successfully created a semi-automated imaging system whose algorithm-based ordinal values for Her-2/neu both strongly correlated with the subjective measurements (intraclass correlation: 0.84;95% confidence interval: 0.79-0.89) yet exhibited no run variability. In addition, the algorithms generated immunocytochemical measurements of Her-2/neu on an expanded continuous scale, which more reliably distinguished true Her-2/neu positivity from true Her-2/neu negativity (determined by FISH) than subjective or algorithmic ordinal scale measurements. Furthermore, the continuous scale measurements could better resolve different levels of Her2/neu overexpression than either subjective or algorithmic ordinal interpretation. Other semi-automated analysis systems have been used to measure Her-2/neu and other cellular immunoreactivities, but these either have required proprietary hardware or hav
Based on the S-tree, the modified S-tree is a newly proposed spatial data structure for representing digital binary images, which can support fast search and query in pictorial database. In this paper, we first presen...
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Based on the S-tree, the modified S-tree is a newly proposed spatial data structure for representing digital binary images, which can support fast search and query in pictorial database. In this paper, we first present a new spatial data structure called the compact S-tree to represent binary images, which uses less memory when compared to the modified S-tree. We then present a fast search algorithm on the compact S-tree, Further, the application to neighbor finding is also investigated. Experimental results show that the proposed search algorithm is faster than the previous known results on the S-tree and the modified S-tree. (C) 1997 Elsevier Science B.V.
This paper introduces the mesh with reconfigurable bus (reconfigurable mesh) as a model of computation. The reconfigurable mesh captures salient features from a variety of sources, including the CAAPP, CHiP, polymorph...
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This paper introduces the mesh with reconfigurable bus (reconfigurable mesh) as a model of computation. The reconfigurable mesh captures salient features from a variety of sources, including the CAAPP, CHiP, polymorphic-torus network, and bus automaton. It consists of an array of processors interconnected by a reconfigurable bus system, which can be used to dynamically obtain various interconnection patterns between the processors. In this paper, we introduce a variety of fundamental data-movement operations for the reconfigurable mesh. Based on these operations, we also introduce new algorithms that are efficient for solving a variety of problems involving graphs and digitized images. The algorithms we present are asymptotically superior to those previously obtained for the aforementioned reconfigurable architectures, as well as to those previously obtained for the mesh, the mesh with multiple broadcasting, the mesh with multiple buses, the mesh-of-trees, and the pyramid computer, to name a few. Highlights include a logarithmic time algorithm to label the connected components of a graph given its adjacency matrix, as well as polylogarithmic time algorithms to solve problems involving convexity and connectivity of figures in images. We also show the power of reconfigurability by solving some problems, such as exclusive OR, more efficiently on the reconfigurable mesh than is possible on the PRAM.
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