Brightness Threshold Research Articles

Genetic Aspects of Mammographic Density Measures Associated with Breast Cancer Risk.

Simple SummaryMammogram risk scores, based on the area of a mammogram covered by white or bright areas defined at different levels of pixel brightness, predict breast cancer risk. They are correlated in relatives, and this might be due to genetic factors that cause breast cancer. We found that the known genetic markers associated with breast cancer risk were weakly correlated with the studied mammogram risk scores. Our findings suggest that less than 1% of the variance of the studied mammogram risk scores is explained by the known genetic markers associated with breast cancer risk. Discovering the genetic determinants of the bright, not white, regions of a mammogram could reveal new information about the genetic causes of breast cancer.Cumulus, Altocumulus, and Cirrocumulus are measures of mammographic density defined at increasing pixel brightness thresholds, which, when converted to mammogram risk scores (MRSs), predict breast cancer risk. Twin and family studies suggest substantial variance in the MRSs could be explained by genetic factors. For 2559 women aged 30 to 80 years (mean 54 years), we measured the MRSs from digitized film mammograms and estimated the associations of the MRSs with a 313-SNP breast cancer polygenic risk score (PRS) and 202 individual SNPs associated with breast cancer risk. The PRS was weakly positively correlated (correlation coefficients ranged 0.05–0.08; all p < 0.04) with all the MRSs except the Cumulus-white MRS based on the “white but not bright area” (correlation coefficient = 0.04; p = 0.06). After adjusting for its association with the Altocumulus MRS, the PRS was not associated with the Cumulus MRS. There were MRS associations (Bonferroni-adjusted p < 0.04) with one SNP in the ATXN1 gene and nominally with some ESR1 SNPs. Less than 1% of the variance of the MRSs is explained by the genetic markers currently known to be associated with breast cancer risk. Discovering the genetic determinants of the bright, not white, regions of the mammogram could reveal substantial new genetic causes of breast cancer.

Crack Repair Model of Ancient Ceramics Based on Digital Image

Ancient ceramics is an important carrier of concretization and artistic transformation of Traditional Chinese culture. It is also an extremely indispensable link for the world to understand traditional Chinese culture. It is of great significance to ensure the quality of ceramic products and improve the reliability of products by nondestructive testing of ceramic microdefect cracks. It is necessary to extract the microdefect crack area first and describe the characteristics of the ceramic crack image with the gradient weighting feature of the model to complete the nondestructive detection of the crack image. The traditional method sets the pixel point and brightness threshold according to the pixel value of the microdefect area but ignores the description of the weighted feature of the image and completes the nondestructive detection of the microdefect crack image of ceramic products. In this study, the improved algorithm of edge detection based on cluster analysis was applied to the ancient ceramic crack repair. First, cluster analysis is used to optimize the Sobel operator in edge detection. Then, the gray value distribution of edge detection map is changed by the Clustering algorithm. Finally，the experimental results show that the contour crack trace and edge direction of the improved edge detection map are obviously enhanced by 20%, which is beneficial to improve the accuracy of ancient ceramic crack repair.

ALGORITHM FOR THE IDENTIFICATION OF EXUDATES IN IMAGES OF THE HUMAN RETINA

Diabetic retinopathy is a complication of diabetes that affects the human eye. One of the very first signs of the disease is the appearance of a wound (exudate), which occurs due to the presence of changes in the blood vessels. Early detection of exudates will reduce the likelihood of developing blindness in patients with diabetic retinopathy. One of the problems in the process of detecting exudates is that the size of the object is quite small compared to the general image, so the task of detecting them is relevant at the present time. This article proposes an algorithm for identifying exudates in images of the human retina. This algorithm includes three main stages, namely: removal of the optic nerve head, determination of the location of the exudate and segmentation of the exudate. Optical disc removal is performed using the middle circle algorithm. In the step of detecting the location of the exudate, the image will be divided into smaller images and then classified into an exudate area and a non-exudate area based on the brightness threshold. Segmentation of the area of exudate is performed using the method of visibility. The study of the operation of the algorithm was carried out on a sample from the DIARETDB1 database by calculating the values of accuracy, sensitivity and specificity. The average accuracy of the proposed algorithm reached 99,33 %, the sensitivity and specificity of the proposed algorithm was 81,65 % and 99,42 %, respectively, which shows that the proposed method can segment exudate well.

Plasmonic random laser enabled artefact-free wide-field fluorescence bioimaging: uncovering finer cellular features.

Narrow bandwidth, high brightness, and spectral tunability are the unique properties of lasers that make them extremely desirable for fluorescence imaging applications. However, due to the high spatial coherence, conventional lasers are often incompatible for wide-field fluorescence imaging. The presence of parasitic artefacts under coherent illumination causes uneven excitation of fluorophores, which has a critical impact on the reliability, resolution, and efficiency of fluorescence imaging. Here, we demonstrate artefact-free wide-field fluorescence imaging with a bright and low threshold silver nanorod based plasmonic random laser, offering the capability to image finer cellular features with sub-micrometer resolution even in highly diffusive biological samples. A spatial resolution of 454 nm and up to 23% enhancement in the image contrast in comparison to conventional laser illumination are attained. Based on the results presented in this paper, random lasers, with their laser-like properties and spatial incoherence are envisioned to be the next-generation sources for developing highly efficient wide-field fluorescence imaging systems having high spatial and temporal resolution for real-time, in vivo bioimaging.

Registration of the time dependence of the number of emission sites as a tool for analyzing field cathodes current fluctuations

A new tool for obtaining the frequency characteristics of the interaction of emission sites with adsorbates was developed. The technique is based on the use of a computerized field projector with online processing of patterns of the distribution of emission sites over the cathode surface. The resulting dependences reflect the frequency of fluctuations in the activity of individual sites. The influence of the choice of the threshold brightness parameter, the proximity of the sites to each other and the stability of the total emission current on the shape of these curves is considered. The coincidence of the shapes of curves constructed by various methods (in online mode, in post-processing mode and in the mode of random processes modeling) is analyzed. Keywords: field emission, emission current fluctuations, carbon nanotubes, registration of emission sites, adsorption processes on the surface.

Emission Brightness and Concentration Quenching Threshold of GdVO4 : Eu3+ Nanophosphors Co‐Doped with Alkali Metal Ions

AbstractGdVO4 : Eu3+ nanophosphors co‐doped with alkali metal ions (Li+, Na+, K+) of various concentrations were fabricated by an efficient hydrothermal method. The microstructure and luminescent emission properties were tested systematically. The results demonstrated that the co‐doping of M+ led to lattice distortion, which is closely related to dopants’ ionic radii and concentrations. The lattice distortion further resulted in a fluctuation of luminescent brightness. The optimal luminescent properties of GdVO4 : Eu3+ co‐doped with Li+(10 atom‐% (at. %)), Na+(8 at. %), K+(6 at. %) were achieved respectively. Among them, the GdVO4 : Eu3+ co‐doped with Li+ of 10 at % possessed the highest emission intensity. Moreover, the alkali metal ions co‐doping also gave rise to the elevation of the concentration quenching threshold of Eu3+, which further enhanced the luminescent performance.

Software and technological complex of identification of sea vessels based on the use of radar space images Sentinel 1

The paper considers the problem of using images from SAR satellites for the identification of seagoing vessels. It describes the main functions of software and technological complex of the automated monitoring. The system is operated with utilizing space images of SAR satellites Sentinel 1A (B). The algorithmic part, which implements the detection on the sea surface the marks associated with ships, is described in details. To reduce the impact of speckle-noise, the image is pre-processed with the improved Lee-filter. Further processing lies in using an adaptive threshold algorithm that provides detection for each local background fragment of the image the unusually bright pixels, at the same time the algorithm provides a constant probability of error. By solving a nonlinear equation, for each position of the background window the algorithm finds the threshold brightness value and then all pixels above this value are considered vessels. In advance the evaluation of parameters of statistical distribution of pixels’ brightness is performed for each position of the background window. K-mean is used for such distribution. The selected bright pixels are combined into compact groups and their size and coordinates are being determined. The obtained results are compared with the data of the AIS, Automatic Identification System of ships, and the results are displayed on a cartographic basis.

Research on Discrimination Threshold of Brightness for Different Color Temperatures

This article explores the experimental study on the relationship between human eye discrimination threshold of white light under different lighting levels and color temperatures by the psychophysical experimental method. The visual matching method was applied to study the subjective brightness perception under different lighting environments. We try to explore the internal connection between the physical intensity and subjective rating value. The experimental results will do help the development of dimming system for smart lighting.

Flickering around the outburst cycle in Kepler dwarf novae

ABSTRACTTaking advantage of the unparalleled quantity and quality of high-cadence Kepler light curves of several dwarf novae, the strength of the flickering and the high-frequency spectral index of their power spectra are investigated as a function of magnitude around the outburst cycle of these systems. Previous work suggesting that the flickering strength (on a magnitude scale) is practically constant above a given brightness threshold and only rises at fainter magnitudes is confirmed for most of the investigated systems. As a new feature, a hysteresis in the flickering strength is seen in the sense that at the same magnitude level flickering is stronger during decline from outburst than during the rise. A similar hysteresis is also seen in the spectral index. In both cases, it can qualitatively be explained under plausible assumptions within the disc instability model model for dwarf nova outbursts.

Division of images into areas of local extrema with a monotonic change in pixel brightness

In this paper, the problem of segmentation of halftone images is considered, in which areas of local maxima and minima (extrema) are distinguished with a monotonic change in the brightness of pixels from local extrema to the boundaries of areas. To solve this problem, a mathematical model is proposed and a segmentation algorithm is developed on the basis of counter-wave growing of local extremum regions. The developed algorithm differs from the known segmentation algorithms by using a set of brightness thresholds (by the number of regions), varying by one in each cycle, starting from the values of local extrema, taking into account the increase or decrease in brightness to select adjacent pixels that are attached to the regions formed from these local extrema. The algorithm provides a greater deviation of pixel brightness from the average value within the region compared to known segmentation algorithms. This does not allow evaluating its efficiency using known indicators based on the variance of the brightness within the region. In this regard, estimates of the monotonicity of changes in the brightness of regions are proposed based on a) the shortest distances from each pixel of the region to the corresponding local extremum along the routes determined by the maximum increase (for the region of the local maximum) or decrease (for the region of the local minimum) the brightness of pixels and b) taking into account the number pixels that break the monotony of the segment brightness change. Using these estimates, it is shown that the proposed algorithm provides segmentation of artificial and natural grayscale images with a monotonic change in the brightness of pixels in the areas of local extrema. These properties allow us to consider the developed algorithm as a basis for the selection of texels, spots, low-contrast objects in images.

Automated detection and classification of galaxies based on their brightness patterns

Clues and traces of the universe's origin and its developmental process are deeply buried in galaxy shapes and formations. Automated galaxies classification from their images is complicated due to the faintness of the galaxy images, conflicting bright background stars, and image noise. For this purpose, the current work proposes a novel logically structured modular algorithm that analyses galaxy morphological raw brightness data to automatically detect galaxy visual center, region, and classification. First, a novel selective brightness threshold is employed to eliminate the effect of bright background stars on detecting galaxy visual centers. Second, a galaxy region detection technique is developed. Finally, a novel technique based on galaxy brightness variation patterns is employed for galaxies classification. The current work has been tested with a run on a collection of 1000 galaxies from the EFIGI catalog. Results demonstrated a success rate of 97.2% in galaxies classification with an average processing time of 0.37 s per galaxy. The high success rates and the low processing time proved the efficiency of the proposed work.

DAWIS: a detection algorithm with wavelets for intracluster light studies

Context. Large numbers of deep optical images will be available in the near future, allowing statistically significant studies of low surface brightness structures such as intracluster light (ICL) in galaxy clusters. The detection of these structures requires efficient algorithms dedicated to this task, which traditional methods find difficult to solve. Aims. We present our new detection algorithm with wavelets for intracluster light studies (DAWIS), which we developed and optimized for the detection of low surface brightness sources in images, in particular (but not limited to) ICL. Methods. DAWIS follows a multiresolution vision based on wavelet representation to detect sources. It is embedded in an iterative procedure called synthesis-by-analysis approach to restore the unmasked light distribution of these sources with very good quality. The algorithm is built so that sources can be classified based on criteria depending on the analysis goal. We present the case of ICL detection and the measurement of ICL fractions. We test the efficiency of DAWIS on 270 mock images of galaxy clusters with various ICL profiles and compare its efficiency to more traditional ICL detection methods such as the surface brightness threshold method. We also run DAWIS on a real galaxy cluster image, and compare the output to results obtained with previous multiscale analysis algorithms. Results. We find in simulations that DAWIS is on average able to separate galaxy light from ICL more efficiently, and to detect a greater quantity of ICL flux because of the way sky background noise is treated. We also show that the ICL fraction, a metric used on a regular basis to characterize ICL, is subject to several measurement biases on galaxies and ICL fluxes. In the real galaxy cluster image, DAWIS detects a faint and extended source with an absolute magnitude two orders brighter than previous multiscale methods.

Design and Implementation of Brightness Configurable Bi-Histogram Equalization Based on FPGA

In order to improve the contrast of images in different brightness environments, based on brightness preserving Bi-Histogram Equalization(BBHE), a Brightness configurable Bi-Histogram Equalization(BCBHE) system is proposed and implemented by FPGA in this paper. The system implements the BBHE algorithm, and adds the brightness configurable logic unit to realize the brightness configurable image contrast enhancement. The test results of the video processing platform of Genesys 2 development board show that: the design obtains BBHE images with different brightness configurations, and achieves the best contrast enhancement visual effect by setting image brightness threshold in different field environment. At the same time, based on the parallel operation characteristics of the FPGA, it meets the requirements of real-time image processing.

A comparative study of the strength of flickering in cataclysmic variables

ABSTRACT Flickering is a universal phenomenon in accreting astronomical systems that still defies detailed physical understanding. It is particularly evident in cataclysmic variables (CVs). Attempting to define boundary conditions for models, the strength of the flickering is measured in several thousand light curves of more than 100 CVs. The flickering amplitude is parametrized by the full width at half-maximum of a Gaussian fit to the magnitude distribution of data points in a light curve. This quantity requires several corrections before a comparison between different sources can be made. While no correlations of the flickering strength with simple parameters such as component masses, orbital inclination, or period were detected, a dependence on the absolute magnitude of the primary component and on the CV subtype is found. In particular, flickering in VY Scl type novalike variables is systematically stronger than in UX UMa type novalikes. The broad-band spectrum of the flickering light source can be fit by simple models but shows excess in the U band. When the data permitted to investigate the flickering strength as a function of orbital phase in eclipsing CVs, such a dependence was found, but it is different for different systems. Surprisingly, there are also indications for variations of the flickering strength with the superhump phase in novalike variables with permanent superhumps. In dwarf novae, the flickering amplitude is high during quiescence, drops quickly at an intermediate magnitude when the system enters into (or returns from) an outburst and, on average, remains constant above a given brightness threshold.

Robust Analysis and Laser Stripe Center Extraction for Rail Images

In this paper, a novel method for the effective extraction of the light stripes in rail images is proposed. First, a preprocessing procedure that includes self-adaptive threshold segmentation and brightness enhancement is adopted to improve the quality of the rail image. Secondly, center of mass is utilized to detect the center point of each row of the image. Then, to speed up the procedure of centerline optimization, the detected center-points are segmented into several parts based on the geometry of the rail profile. Finally, piecewise fitting is adopted to obtain a smooth and robust centerline. The performance of this method is analyzed in detail, and experimental results show that the proposed method works well for rail images.

An Ultradeep Multiband VLA Survey of the Faint Radio Sky (COSMOS-XS): Source Catalog and Number Counts

Abstract We present ultradeep, matched-resolution Karl G. Jansky Very Large Array observations at 10 and 3 GHz in the COSMOS field: the COSMOS-XS survey. The final 10 and 3 GHz images cover ∼16 and and reach median rms values at the phase center of 0.41 and 0.53 μJy beam−1, respectively. Both images have an angular resolution of ∼20. To account for the spectral shape and resolution variations across the broad bands, we image all data with a multiscale, multifrequency synthesis algorithm. We present source catalogs for the 10 and 3 GHz image with 91 and 1498 sources, respectively, above a peak brightness threshold of 5σ. We present source counts with completeness corrections included that are computed via Monte Carlo simulations. Our corrected counts at 3 GHz are consistent within the uncertainties with other results at 3 and 1.4 GHz but extend to fainter flux densities than previous direct detections. The 3 GHz number counts exceed the counts predicted by the semiempirical simulations developed in the framework of the SKA Simulated Skies project, consistent with previous P(D) analyses. Our source counts suggest a steeper luminosity function evolution for faint star-forming sources. The semiempirical Tiered Radio Extragalactic Continuum Simulation predicts this steeper evolution and is in better agreement with our results at 10 and 3 GHz within the expected variations from cosmic variance. In summary, the multiband, matched-resolution COSMOS-XS survey in the COSMOS field provides a high-resolution view of the ultrafaint radio sky that can help guide next-generation radio facilities.

Регистрация зависимости числа эмиссионных центров от времени как инструмент анализа токовых флуктуаций полевых катодов

A new tool for obtaining the frequency characteristics of the interaction of emission sites with adsorbates was developed. The technique is based on the use of a computerized field projector with online processing of patterns of the distribution of emission sites over the cathode surface. The resulting dependences reflect the frequency of fluctuations in the activity of individual sites. The influence of the choice of the threshold brightness parameter, the proximity of the sites to each other and the stability of the total emission current on the shape of these curves is considered. The coincidence of the shapes of curves constructed by various methods (in online mode, in post-processing mode and in the mode of random processes modeling) is analyzed.

Volume increasing of secret message in a fixed graphical stego container based on intelligent image analysis

The paper considers methods of edge pixel selection based on Roberts, Previtt, and Sobel operators, as well as technologies of cellular automata to increase the volume of the implemented secret message. Based on the methods used, templates with selected pixels were formed, into the codes of which secret message bits were embedded. The templates were formed using threshold additional processing, which allowed to select the optimal threshold for the selection of the corresponding pixels of the image of the container. Thresholds ranging from 100 to 300 were selected for the Roberts operator, and thresholds ranging from 1,000,000 to 15,000,000 were selected for the Previtt and Sobel operator. To select pixels based on cell technology, four cell neighborhood shapes were used for binary and color imaging. Experimental studies were performed for all methods of pixel selection, which made it possible to determine the optimal numerical threshold, as well as the number of lower bits of each selected pixel to implement the bits of the secret message. It has been experimentally established that for all methods, except for the two lower bits of the code of each pixel, the bits of the secret message are also embedded in the four lower bits of each byte of code of the selected pixel, which significantly increases the volume of the embedded message. When using two lower bits of all pixels and four lower bits of selected pixels for many templates, no change in the visual images of the containers was observed. Using the fifth lower bit in each byte of the selected pixel code to enter the secret bit results in significant distortion of the visual picture. The experiments were performed for different brightness thresholds during binarization. In total, six additional secret bits were added to the code of each selected pixel. For the efficiency of the experiments, bit sequences containing only one zero, one unit, and randomly generated bit sequences were introduced into the containers.

Fractal analysis of human cerebellum based on magnetic resonance imaging data: pixel dilating method

Background. The use of fractal analysis as a morphometric method allows to investigate biological structures that have the properties of fractals, including the human cerebellum. Adaptation of fractal analysis techniques to assess the state of brain structures using magnetic resonance imaging is an important area of modern morphology. Objective: to determine the values of the fractal dimension (FD) of the cerebellar tissue measured by magnetic resonance imaging using the pixel dilation. Methods. The study was conducted on magnetic resonance images of the brain of 120 relatively healthy patients. Fractal analysis of digital magnetic resonance images of the cerebellum was performed using the method of pixel dilation in the author's modification. Results. It was found that the average value of FD of the cerebellar vermis on the midsagittal section on T2 weighed images with a brightness threshold of 100 was 1.691 ± 0.01. The FD values of the cerebellar hemisphere tissue were: in the paravermal zone on the left 1.683 ± 0.01, on the right 1.685 ± 0.01; in the central zone of the hemisphere on the left 1.679 ± 0.01, on the right 1.672 ± 0.01; on the lateral zone of the hemisphere on the left 1.665 ± 0.01, on the right 1.682 ± 0.01. These values do not differ statistically significantly in the symmetrical areas of the right and left hemispheres and do not differ from the FD values of the cerebellar vermis. Conclusion. The method of pixel dilation of fractal analysis can be used for morphometric study of magnetic resonance images of the brain. Fractal analysis allows an objective assessment of the morphofunctional condition of the cerebellum, which can be used to diagnose various diseases of the cerebellum and other CNS structures.

Fractal dimension of the cortex and white matter of human cerebellum (magnetic resonance imaging study)

The cerebellum is a typical structure with fractal properties, so fractal analysis is one of the main morphometric techniques that allow a comprehensive assessment of its morphofunctional state; the development of methods for differential measurement of the fractal dimension of various components of cerebellar tissue is necessary for complex morphological examination of the cerebellum using fractal analysis. The aim of the study was to develop an algorithm for differential fractal analysis and to determine the values of the fractal dimension of the cortex and white matter of human cerebellum using the study of magnetic resonance imaging scans. Digital T2 weighted magnetic resonance imaging scans of 30 conditionally healthy persons were used in the study. Fractal analysis of the distinct components of the cerebellar tissue was performed using the pixel dilation method. The fractal dimension values for all threshold brightness values (from 0 to 255) were determined. The confidence interval of the fractal dimension values based on the average values of the fractal dimension of the entire range of brightness values was calculated. Algorithms for image preprocessing were developed for an individual study of the different components of the cerebellum: cerebellar tissue as a whole, white matter, molecular and granular layers of the cortex. A differential fractal analysis technique has been developed to assess individual components of the cerebellar tissue. The values of the fractal dimension of white matter, granular and molecular layers of the cerebellar cortex were determined. The values of the fractal dimension of cerebellar tissue as a whole and the fractal dimension of the cerebellar cortex as a whole were the biggest. These values exceed the value of the fractal dimension of white matter. The average value of the fractal dimension (FD) for the threshold value of 80 (white matter) was 1.318±0.050, for the value of 90 (white matter and the granular layer of the cortex) was 1.568±0.028, for the value of 100 (cerebellar tissue as a whole) was 1.694±0.010. The average FD of the granular layer of the cortex (brightness range 81-90) was 1.377±0.020, the FD of the molecular layer of the cortex (brightness range 91-100) was 1.353±0.020, the average FD of the cerebellar cortex as a whole (brightness range 81-100) was 1.564±0.018. The obtained data can be used as diagnosis criteria to assess the morphofunctional state of the cerebellum using magnetic resonance imaging.