Pixel Standard Deviation Research Articles

Measures for the Integration of Digital Media Art and Film and Animation Creation Based on Virtual Reality Technology

Abstract In this paper, we propose a scene animation network (FSGAN) method that uses spectral features to perceive the deep style of an image, which uses three loss functions for perceiving the distribution of image style features in the same style domain to generate anime style-consistent images. The recurrent consistency adversarial network is supplemented with a local reinforcement module based on self-attention, adapted to the animalization of portrait scenes based on their characteristics and needs. This module guides the network to pay attention to the salient regions in the image and combines layer normalization and instance normalization methods through the weighting of the attention weight coefficients to construct a portrait animation network based on local reinforcement perception. Then, based on the digital media technology to complete the virtual reality scene construction, the constructed space for three-dimensional division, and the use of generative adversarial network training model, the proposed key events and random sampling technology combined with the control of virtual animation scene generation method, to achieve the controllability and diversity of the virtual animation scene generation. The first-stage design efficiency, the second-stage design efficiency and the overall design efficiency of the animation creation method in this paper are all basically stabilized between 0.8-1. Compared with the traditional method, they are higher by 0.3932, 0.3596, and 0.5635, respectively. The extreme pixel percentage, standard deviation and contrast of the animation images created by this paper’s method are 0.0349, 0.0037 and 0.3382, respectively, and the overall color performance is better. Thus, the method presented in this paper has the best overall effect on processing anime images using digital media art effects.

A Preliminary Study of the Relationships Between Echotextural Characteristics of the Mammary Gland and Chemical Composition of Milk During Early Lactation in EWES

Abstract This study aimed to examine the ultrasonographic characteristics of the mammary gland in post-partum ewes (1 to 4 weeks after lambing) of varying genotypes for correlations with the chemical composition of milk. Ultrasonograms of mammary glands in coronal (C) and sagittal (S) planes were obtained using 5.0- and 7.5-MHz transducers from four polish mountain (PMt) and six Olkuska (Olk) ewes. Computerized image analyses of all images have been performed to determine pixel intensity (numerical pixel values – NPV) and heterogeneity (pixel standard deviation – PSD) of the mammary gland stroma/parenchyma. In PMT ewes examined with the 5.0-MHz probe, the mean NPV-C correlated negatively with C17:0 (margaric acid) and C17:1 C10 (heptadecenoic acid). Furthermore, NPV-s correlated negatively with C17:0 content of milk. In PMT ewes examined with the 7.5-MHz transducer, the mean NPV-S correlated positively with the crude fat and total solids, and negatively with C18:3 c9, C12, C15 (N-3) (α-linoleic acid) content of milk samples, while PSD-S correlated positively with C16:0 (palmitic acid) and negatively with lactose. In the scans obtained with the 5.0-MHz in olk sheep, the mean NPV-C was directly related to C10:1 (decanoic acid), C14:1 (myristoleic acid), C16:1 iso (iso-hexadecanoic acid), C16:1 C9 (palmitoleic acid), and c18:0 (stearic acid) content; the mean psd-c correlated positively with total solids, c14:1, C15:0, C16:0, C16:1 iso, C16:1 C9, ClA (conjugated linoleic acids), and total saturated fatty acid content, and negatively with C18:1 C11 (N-7) (cis-vaccenic acid), C18:2 C9, C12 (n-6) (linoleic acid), and total polyunsaturated fatty acid content of milk; and the mean psd-s correlated directly with ash and total saturated fatty acid content of the milk. Lastly, the mean NPV-C of images recorded with the 7.5-MHz probe in olk ewes related directly to ash and C12:0 (lauric acid); the mean NPV-S related directly to ash and C16:1 iso; the mean PSD-C correlated positively with ash and total saturated fatty acid (SFA) content, and the mean PSD-S correlated positively with the total SFA. Echotextural attributes of the mammary gland in ewes have the makings of the technique for determining milk content of certain chemical constituents in a breed-specific manner; however, further studies are needed to verify the usefulness of echotextural analyses of the udder to consistently predict complete milk composition.

Udder Ultrasonography of Dairy Cows: Investigating the Relationship between Echotexture, Blood Flow, Somatic Cell Count and Milk Yield during Dry Period and Lactation.

Udder health of dairy cows is related to their productivity and welfare. The period from dry-off to calving and early lactation is crucial. Ultrasonography is a useful and practical tool for the examination of the mammary parenchyma and blood flow. This observational study investigated the relationship between udder echotexture features, blood flow volume (BFVol) in the milk vein, milk somatic cell count (SCC) and daily milk yield (DMY) from late lactation, throughout the dry period and consecutive early lactation. Seventeen repeated measurements were performed on twenty-one Holstein cows. The udder parenchyma was examined with B-mode ultrasonography. Udder echotexture was studied using 15 features: Numerical Pixel Value (NPV), Pixel Standard Deviation (PSD), Skewness, Excess, Contrast, Homogeneity, Correlation, Entropy, Run Percentage, Long-Run Emphasis, Grey Value Distribution, Runlength Distribution, Gradient Mean Value, Gradient Variance and Percentage of Non-zero Gradients. Blood flow in the milk vein was examined with spectral Doppler. Linear mixed-effects models were employed to investigate relationships between BFVol, udder echotexture features, SCC and DMY throughout the study period. Our models showed that a 1 kg increase in DMY was associated with a significant increase of 0.25 L/min in the expected BFVol and that a 1,000,000-cells/mL increase in SCC was associated with a significant BFVol decrease of 0.49 L/min, keeping all other variables constant. Multivariable models showed significant associations between DMY and NPV, between PSD and Long-Run Emphasis, and between SCC and NPV, PSD, Gradient Mean Value, Homogeneity, Gradient Variance and Entropy. In conclusion, udder echotexture and BFVol in the milk vein are related to SCC and milk yield. Ultrasonography can be used for the comprehensive assessment of udder health in support of precision dairy farming.

Magneto-optical imaging nondestructive testing of welding defects based on image fusion

Improving the visual effect of welding defect detection is a key research area of magneto-optical imaging nondestructive testing technology. Finite element analysis and magneto-optical image simulation are used to analyze the characteristics of magneto-optical imaging detection under rotating excitation. Through the stripe analysis of simulated magneto-optical images, it is found that the multi-frame magneto-optical images at defects have low discrete degree of gray value. Therefore, an image fusion method based on pixel standard deviation is proposed for the welding defect detection of magneto-optical imaging. Fast guide filtering is applied to the magneto-optical images of welding defects under rotating excitation. Pixel standard deviation is used to fuse multi-frame magneto-optical images, and image enhancement and rendering are used to improve the visual effect of welding defect detection. The experimental results show that the fast guided filter can improve the speed of image preprocessing and ensure good image smoothing effect. Compared with other image fusion algorithms, the proposed method can significantly improve the image quality of magneto-optical imaging detection, and does not require screening of magneto-optical images. This method has the advantages of tolerating frame drops in acquisition and excellent generalization performance, enabling fast and efficient nondestructive testing of welding defects.

MP09-20 CONTRAST AGENTS FOR UROLOGIC FLUOROSCOPY: A COMPARATIVE PHANTOM STUDY

You have accessJournal of UrologyCME1 Apr 2023MP09-20 CONTRAST AGENTS FOR UROLOGIC FLUOROSCOPY: A COMPARATIVE PHANTOM STUDY Anahita Heshmat, Gene Austin, Manuel Arreola, and Benjamin Canales Anahita HeshmatAnahita Heshmat More articles by this author , Gene AustinGene Austin More articles by this author , Manuel ArreolaManuel Arreola More articles by this author , and Benjamin CanalesBenjamin Canales More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003224.20AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: The recent international shortage of iodinated contrast agents has driven many clinicians to search for alternative agents to image a variety of urologic conditions in order to maintain clinic workflow. We sought to standardize these agents by a quantitative comparison using a phantom model. METHODS: A donut shape gel phantom with 10-mm wide plastic rods filled with Omnipaque-300, Omnipaque-350, Visipaque-270, Isovue-370, Gadavist, Eovist, and liquid water, was used to represent a patient being imaged for an urethrogram study utilizing a mobile fluoroscopy. The phantom was imaged with various acquisitions (Auto tube voltage (kVp), tube current (mA), and various dose modes, frame rates, and magnification modes) to compare and asses image quality for different contrast agents. Quantitative evaluations were performed with extracting regions of interest (ROIs) of each contrast rod to gather mean pixel values and standard deviations. These ROI measurements were then utilized to calculate contrast-to-noise ratio (CNR) as the metric appropriate for image quality evaluation. RESULTS: The mean pixel and CNR values of Omnipaque-300, Omnipaque-350, Visipaque-270, Isovue-370, and Gadavist showed no difference in visibility among these five contrast agents while using different dose modes, frame rates, and magnification modes. However, that was not the case for Eovist as its mean pixel value and CNR value were close to those of liquid water. Furthermore, changing magnification from normal to magnification 1 and magnification 2 increased the mean pixel values and CNR values at normal dose and continuous frame rate. CONCLUSIONS: With the exception of Eovist, the iodinated and gadolinium-based contrast agents we tested can be interchanged without compromising visibility or image quality based upon this comparative phantom study. Source of Funding: None © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e113 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Anahita Heshmat More articles by this author Gene Austin More articles by this author Manuel Arreola More articles by this author Benjamin Canales More articles by this author Expand All Advertisement PDF downloadLoading ...

Estimation of dissolved organic carbon from inland waters at a large scale using satellite data and machine learning methods

Dissolved Organic Carbon (DOC) in inland waters plays an essential role in the global carbon cycle and has significant public health effects. Machine learning (ML) together with remote sensing has emerged as a powerful and promising combination to quantify water quality parameters from space. However, inland water sample data for DOC is limited. Hence, little is known about the potential to quantify DOC content in inland waters, especially over large-scale areas. This study presents the first attempt to estimate DOC in inland waters over a large-scale area using satellite data and ML methods with the newly published open-source dataset AquaSat. Four ML approaches, namely Random Forest Regression (RFR), Support Vector Regression (SVR), Gaussian Process Regression (GPR), and a Multilayer Backpropagation Neural Network (MBPNN) were trained using more than 16 thousand samples across the continental United States matched with satellite data from Landsat 5, 7 and 8 missions. Satellite data from the Landsat missions were further extended with environmental data from the ERA5-Land product and used as input to train the ML algorithms. Our results show that including environmental data as inputs considerably improved the prediction of DOC for all ML algorithms, with GPR showing the most promising performance results with moderate estimation errors (RMSE: 4.08 mg/L). Permutation feature importance analysis showed that the wavelength range in the visible Green band (from Landsat) and the monthly average air temperature (from ERA5-Land) were the most important variables for the ML approaches. The results demonstrate the predictive strength of GPR and its useful feature to derive per pixel standard deviations for detailed analysis. Our results further highlight the important role of considering environmental processes to explain DOC variations over large scales. The application and performance of the GPR in mapping spatiotemporal variations of DOC in an entire water body were discussed by taking Lake Okeechobee (the 8th largest freshwater lake in the U.S.) as an illustrative example. While performance evaluation showed that DOC concentrations can be retrieved with adequate accuracy, algorithm development was challenged by the heterogenous nature of large-scale open source in situ data, issues related to atmospheric correction, and the low spatial and temporal resolution of the environmental predictors. This research demonstrates how open source, large-scale datasets like AquaSat in combination with ML and satellite remote sensing can make research toward large-scale estimation of inland water DOC more realistic while highlighting its remaining limitations and challenges.

A Case Study of Vignetting Nonuniformity in UAV-Based Uncooled Thermal Cameras

Uncooled thermal cameras have been employed as common UAV payloads for aerial temperature surveillance in recent years. Due to the lack of internal cooling systems, such cameras often suffer from thermal-drift-induced nonuniformity or vignetting despite having built-in mechanisms to minimize the noise. The current study examined a UAV-based uncooled thermal camera vignetting regarding camera warmup time, ambient temperature, and wind speed and direction, and proposed a simple calibration-based vignetting migration method. The experiments suggested that the camera needed to undergo a warmup period to achieve stabilized performance. The required warmup duration ranged from 20 to 40 min depending on ambient temperature. Camera vignetting severity increased with camera warmup time, decreasing ambient temperature, and wind presence, while wind speed and direction did not make a difference to camera vignetting during the experiments. Utilizing a single image of a customized calibration target, we were able to mitigate vignetting of outdoor images captured in a 30 min duration by approximately 70% to 80% in terms of the intra-image pixel standard deviation (IISD) and 75% in terms of the pixel-wise mean (PWMN) range. The results indicated that outdoor environmental conditions such as air temperature and wind speed during short UAV flights might only minimally influence the thermal camera vignetting severity and pattern. Nonetheless, frequent external shutter-based corrections and considering the camera nonlinear temperature response in future studies have the potential to further improve vignetting correction efficacy for large scene temperature ranges.

Development of an algorithm to convert mammographic images to appear as if acquired with different technique factors.

Purpose: We set out a fully developed algorithm for adapting mammography images to appear as if acquired using different technique factors by changing the signal and noise within the images. The algorithm accounts for difference between the absorption by the object being imaged and the imaging system. Approach: Images were acquired using a Hologic Selenia Dimensions x-ray unit for the validation, of three thicknesses of polymethyl methacrylate (PMMA) blocks with or without different thicknesses of PMMA contrast objects acquired for a range of technique factors. One set of images was then adapted to appear the same as a target image acquired with a higher or lower tube voltage and/or a different anode/filter combination. The average linearized pixel value, normalized noise power spectra (NNPS), and standard deviation of the flat field images and the contrast-to-noise ratio (CNR) of the contrast object images were calculated for the simulated and target images. A simulation study tested the algorithm on images created using a voxel breast phantom at different technique factors and the images compared using local signal level, variance, and power spectra. Results: The average pixel value, NNPS, and standard deviation for the simulated and target images were found to be within 9%. The CNRs of the simulated and target images were found to be within 5% of each other. The differences between the target and simulated images of the voxel phantom were similar to those of the natural variability. Conclusions: We demonstrated that images can be successfully adapted to appear as if acquired using different technique factors. Using this conversion algorithm, it may be possible to examine the effect of tube voltage and anode/filter combination on cancer detection using clinical images.

Relationship Between Somatic Cell Counts and Mammary Gland Parenchyma Ultrasonography in Buffaloes.

The aim of the present study was to determine whether the echotextural features of the mammary gland parenchyma in buffaloes during lactation at different somatic cell levels could be used to diagnose mastitis. This study was divided into two parts. In the first experiment, experimental buffaloes (n = 65) with somatic cell counts (SCC) tests (n = 94) in different seasons, including spring (n = 22), summer (n = 24), autumn (n = 37), and winter (n = 11), were used to obtain ultrasonic variables for each quarter of mammary gland that could best explain the corresponding somatic cell level. In the second part of the study, the first part's experimental results were verified by subjecting at least one-quarter udder of eight buffaloes to ultrasonography seven times during mid-July to mid-August for obtaining ultrasonic values at different somatic cell levels. The echo textural characteristics [mean numerical pixel values (NPVs) and pixel heterogeneity (pixel standard deviation, PSD)] were evaluated using 16 ultrasonographic images of each buffalo with Image ProPlus software. The effects of SCC, days in milk (DIM), scanning order (SO), season, as well as the scanning plane and udder quarter (SP + UQ) on both the PSD and NPVs of the mammary gland were significant (p < 0.05). The correlation coefficient between pre-milking sagittal PSD and somatic cell score (SCS) was the highest (r = 0.4224, p < 0.0001) with fitted linear model: y = 0.19445x (dependent variable: SCS, independent variables: pre-milking sagittal PSD; R2 = 0.84, p < 0.0001). In addition, SCC and ultrasonic of udder quarter were followed for 1 month, confirming that pre-milking sagittal PSD of mammary gland value could explain the SCC variation in milk. The current study demonstrated that the ultrasonographic examination of the udder could be one of the complementary tools for diagnosing subclinical mastitis in buffaloes.

Examinations for creating an image of unacquired dose from the images of two types of dose in digital radiography.

Digital radiography (DR) is grayscale adjustable and it can be unclear whether an acquired DR image is captured with the minimum radiation dose required. It is necessary to make an image of the amount of noise when taken at a lower dose than the acquired image, without increased exposure. To examine whether an image of unacquired dose can be created from two types of dose DR images acquired using a phantom. To create an additive image from two images of different doses, the pixel value of one image is multiplied by a coefficient and added to the other. The normalized noise power spectra (NNPS) of the normal image and the additive image with the same signal-to-noise ratio (SNR) are compared. The image noise of the unacquired doses is estimated from the graph changes of the pixel values and standard deviations of two images. The error between the SNR of the image obtained by changing the dose and the estimated SNR is measured. We propose a multiplication coefficient calculation formula that theoretically adjusts the additive image to the target SNR. The SNR error of the image created based on this formula is measured. The NNPS curves of the additive and normal images show a difference on the high frequency side. According to the statistics considering the preset of mAs value, there is no significant difference at 85%. The SNR estimation error is approximately 1%. The SNR error of the additive image created based on the formula is approximately 5%. The noise of the image of unacquired dose can be estimated, and the additive image adjusted to this value can be considered equivalent to the image taken at the actual dose.

A Benchmark for automatic noise measurement in clinical computed tomography.

Assessment of image quality directly in clinical image data is an important quality control objective as phantom-based testing does not fully represent image quality across patient variation. Computer algorithms for automatically measuring noise in clinical computed tomography (CT) images have been introduced, but the accuracy of these algorithms is unclear. This work benchmarks the accuracy of the global noise (GN) algorithm for automatic noise measurement in contrast-enhanced abdomen CT exams in comparison to precise reference noise measurements. The GN algorithm was further optimized compared to the previous report in the literature. Reference values of noise were established in a public image dataset of 82 contrast-enhanced abdomen CT exams. The reference noise values were obtained by manual regions-of-interest measurements of pixel standard deviation in the liver parenchyma according to an instruction protocol. Noise measurements taken by six observers were averaged together to improve reference noise statistical precision. The GN algorithm was used to automatically measure noise in each image set. The accuracy of the GN algorithm was determined in terms of RMS error compared to reference noise. The GN algorithm was optimized by conducting 1000 trials with random algorithm parameter values. The trial with the lowest RMS error was used to select optimum algorithm parameters. The range of noise across CT image sets was 8.8-28.8 HU. Reference noise measurements were made with a precision of ±0.78HU (95% confidence interval). The RMS error of automatic noise measurement was 0.93HU (0.77-1.19HU 95% confidence interval). The automatic noise measurements were equally accurate across image sets of varying noise magnitude. Optimum GN algorithm parameter values were: a kernel size of 7 pixels, and soft tissue lower and upper thresholds of 0 and 170HU, respectively. The performance of automatic noise measurement was benchmarked in a large clinical CT dataset. The study provides a framework for thorough validation of automatic clinical image quality measurement methods. The GN algorithm was optimized and validated for automatic measurement of soft-tissue noise in abdomen CT exams.

Spatial Distribution of Noise Reduction in Four Iterative Reconstruction Algorithms in CT-A Technical Evaluation.

Iterative reconstruction (IR) is a computed tomgraphy (CT) reconstruction algorithm aiming at improving image quality by reducing noise in the image. During this process, IR also changes the noise properties in the images. To assess how IR algorithms from four vendors affect the noise properties in CT images, an anthropomorphic phantom was scanned and images reconstructed with filtered back projection (FBP), and a medium and high level of IR. Each image acquisition was performed 30 times at the same slice position, to create noise maps showing the inter-image pixel standard deviation through the 30 images. We observed that IR changed the noise properties in the CT images by reducing noise more in homogeneous areas than at anatomical edges between structures of different densities. This difference increased with increasing IR level, and with increasing difference in density between two adjacent structures. Each vendor’s IR algorithm showed slightly different noise reduction properties in how much noise was reduced at different positions in the phantom. Users need to be aware of these differences when working with optimization of protocols using IR across scanners from different vendors.

Technical Note: Validation of TG 233 phantom methodology to characterize noise and dose in patient CT data.

Phantoms are useful tools in diagnostic CT, but practical limitations reduce phantoms to being only a limited patient surrogate. Furthermore, a phantom with a single cross sectional area cannot be used to evaluate scanner performance in modern CT scanners that use dose reduction techniques such as automated tube current modulation (ATCM) and iterative reconstruction (IR) algorithms to adapt x-ray flux to patient size, reduce radiation dose, and achieve uniform image noise. A new multisized phantom (Mercury Phantom, MP) has been introduced, representing multiple diameters. This work aimed to ascertain if measurements from MP can predict radiation dose and image noise in clinical CT images to prospectively inform protocol design. The adult MP design included four different physical diameters (18.5, 23.0, 30.0, and 37.0cm) representing a range of patient sizes. The study included 1457 examinations performed on two scanner models from two vendors, and two clinical protocols (abdominopelvic with and chest without contrast). Attenuating diameter, radiation dose, and noise magnitude (average pixel standard deviation in uniform image) was automatically estimated in patients and in the MP using a previously validated algorithm. An exponential fit of CTDIvol and noise as a function of size was applied to patients and MP data. Lastly, the fit equations from the phantom data were used to fit the patient data. In each patient distribution fit, the normalized root mean square error (nRMSE) values were calculated in the residuals' plots as a metric to indicate how well the phantom data can predict dose and noise in clinical operations as a function of size. For dose across patient size distributions, the difference between nRMSE from patient fit and MP model data prediction ranged between 0.6% and 2.0% (mean 1.2%). For noise across patient size distributions, the nRMSE difference ranged between 0.1% and 4.7% (mean 1.4%). The Mercury Phantom provided a close prediction of radiation dose and image noise in clinical patient images. By assessing dose and image quality in a phantom with multiple sizes, protocol parameters can be designed and optimized per patient size in a highly constrained setup to predict clinical scanner and ATCM system performance.

Remote sensing for monitoring and mapping Land Productivity in Italy: A rapid assessment methodology

We present a remote sensing-based methodology for the Land Productivity (LP) rapid assessment and monitoring of status and trends at national and sub-national scales. This methodology aims at supporting national and international policies to achieve the Land Degradation Neutrality (LDN) target in the framework of the UN Agenda 2030 and the Sustainable Development Goals (SDG 15.3). The work was performed using the NASA-MODIS Normalized Difference Vegetation Index (NDVI) as proxy indicator of LP status and trends in Italy for 16 years (2000–2015). The assessment of the LP status was based on the pixel mean and standard deviation values of yearly LP values. The LP trends of the yearly time series were computed using Mann-Kendall (MK) and Contextual MK (CMK) tests providing a monitoring indicator for land productivity change. The amount of land with valid increasing and decreasing trends is estimated assuming the 95% significance level of trends in the areas with “good” NDVI pixel reliability. The area of increasing and decreasing LP are estimated for the national territory and for different land covers. The widespread observed increasing LP variations were correlated to the progressive renaturalization of lands subsequent to the decrease of agricultural activities and increasing precipitation trends in the winter season. Decreasing LP affected very limited areas and hot spots were correlated to changes of seasonal precipitation and anthropic activities. The areas and municipalities most affected by LP changes are identified and may support, in the framework of SDG 15.3 and LDN, the identification of policy initiatives.

Testicular Morphological and Ultrasonographic Characterization of Male Gray Brocket Deers (Mazama gouazoubira) in Different Reproductive Status

Background: Gray brocket deer (Mazama gouazoubira) populations have been declining due to human intervention. Yet, only a few studies have assessed ultrasonographic testicular characteristics in cervids. Considering the relevance of monitoring testicular size, blood flow, and parenchyma, the present study aims to establish baseline information on scrotal circumference, testicular volume, and spectral Doppler parameters, to describe differences among adult male gray brocket deer in different reproductive status, and to correlate ultrasound parameters with testes size measurements.Materials, Methods &amp; Results: Six adult male gray brocket deers were used in the study. Scrotal circumference and testicular volume were measured. B mode ultrasound images of testes (longitudinal and cross-sectional views) and epididymes were subjected to computer-assisted analysis, obtaining the numerical pixel values (NPV) and pixel standard deviation (PSD). Using spectral Doppler, supratesticular artery blood flow velocities (peak systolic velocity - PSV, end diastolic velocity - EDV, time-average maximum velocity - TAMAX, resistivity - RI and pulsatility indices - PI) were obtained. Semen was analyzed through total motility, vigor, and concentration tests. Three animals were normospermic (F+ group) and three were oligo/azoospermic (F- group). Groups were compared using were compared using a one-way ANOVA or Kruskal-Wallis followed by Student-Newman-Keuls (SNK) test. Ultrasound parameters were correlated to testes size parameters using Pearson’s correlation for parametric variables and Spearman’s correlation for non-parametric variables. F+ group presented significantly higher scrotal circumference (14.57 ± 1.19 cm), testicular volume (26.18 ± 4.94 cm3), and testes cross-sectional NPV (69.88 ± 24.00) and PSD (10.78 ± 3.42) than group F- (NPV: 28.26 ± 13.75, PSD: 6.70 ± 1.84). No significant differences were observed between the groups regarding the spectral Doppler ultrasound parameters. Significant correlations were observed between scrotal circumference and longitudinal (r = 0.76) and cross-sectional testes NPV (r = 0.89), and testicular volume was correlated with longitudinal (r = 0.78) and cross-sectional testes NPV (r = 0.91) and with cross-sectional testes PSD (ρ = 0.82).Discussion: Increased testicular echogenicity (higher NPV) has been positively associated with improved testicular growth, cell population expansion, inner and outer seminiferous tubules diameter, spermatids percentages and testis weight. In addition, more heterogenous testes (higher PSD) were associated with higher sperm output. It was suggested that the animals in group F- had compromised testicular development and spermatogenesis. The correlation observed between testes NPV and scrotal circumference was proposed to be associated with seminiferous tubules impairment. The F- group showed lower testicular volume, NPVs and PSDs in cross-sectional testicular images, suggesting higher protein levels and lower lipid contents were present in their parenchyma, influencing in testicular echogenicity and echotexture. No differences in spectral Doppler parameters were observed between the two groups. Also observed in stallions. However, PSV, EDV, TAMAX could be potential infertility indicators in other mammalians. These different results may be due to different locations of the evaluated vessel, species and techniques, age, ambient temperature, pathological conditions, and anaesthesia. Thus, it is suggested that scrotal circumference, testicular volume, and testes NPV are good indicators of male reproductive health in gray brocket deer and may help with better male selection in the species.

Detecting historic informal settlement fires with Sentinel 1 and 2 satellite data - Two case studies in Cape Town

Increasing global urbanisation is leading to a rise in the number of people living in informal settlements, challenging our ability to achieve sustainable development goals. As a consequence of high building density, inadequate building methods and flammable building materials, informal settlements are highly vulnerable to the devastating impacts of fire. Databases on historic fire occurrence, location and extent are scarce, especially in the Global South. This paper explores the potential for remote sensing technologies to fill this gap. Two case studies in Cape Town representing fire of different extent and build back characteristics, are used to demonstrate that Sentinel-1 and Sentinel-2 data can be used to detect known historic informal settlement fire. A pixel based approach applied to Sentinel-2 band 2 reflectance and Sentinel 1 backscatter and interferometry are highlighted. The concept of spatial autocorrelation is explored with both Sentinel-2 and 1 data showing that a 3 x 3 pixel standard deviation kernel and hotspot analysis can complement the pixel approach. Further research is required to test these methods within a time series change detection algorithm to identify unknown historic informal settlement fires. .

Non-contact Real-time Heart Rate Measurement Algorithm Based on PPG-standard Deviation

Heart rate is an important physiological parameter for clinical diagnosis, it can infer the health of the human body. Thus, efficient and accurate heart rate measurement is important for disease diagnosis and health monitoring. There are two ways to measure heart rate. One is contact type and the other is non-contact. Contact measurement methods include pulse cutting, electrocardiogram, etc. Because of the inconvenience of this method, a non-contact heart rate method has been proposed. Traditional non-contact measurement method based on image is collecting RGB three-channel signals in continuous video and selecting the average value of the green channel pixels as the heart rate signal for processing. However, this method is not accurate when the pixel values are changing greatly. To overcome this problem, non-contact real-time heart rate measurement method is proposed in this paper based on pixel standard deviation. Because of the changes in skin color caused by heart rate, the standard deviation signal of the green channel pixels in the region of interest (ROI) is filtered and extracted by the forward and inverse Fourier transform respectively, measuring the heart rate. The experimental results show that the improved algorithm can measure heart rate with faster speed and higher accuracy comparing to traditional methods. And we hope that our algorithm can apply in intelligent elder caring.

Quantitative Ultrasound Imaging Pixel Analysis of the Intrinsic Plantar Muscle Tissue between Hemiparesis and Contralateral Feet in Post-Stroke Patients.

Quantitative ultrasound imaging of the muscle tissue may be applied in the neurology field, due to B-mode grayscale pixels values could be used as potential biomarkers for disease progression and intervention effects in poststroke patients. Thus, the study aim was to compare and analyze the ultrasound imaging B-mode pixels differences between the intrinsic plantar muscles cross-sectional area (CSA) in hemiparetic and contralateral feet from poststroke patients by means of the Image J software. A case-control design and a convenience sampling method were used in order to recruit 22 feet from 11 poststroke patients. This total sample was divided into 11 hemiparetic feet and 11 contralateral feet. The Image J software was used in order to evaluate the interface distance, CSA as well as measure the pixels mean, standard deviation (SD) and count from all offline images in the flexor digitorum brevis, abductor hallucis (AbH), and flexor hallucis brevis muscles. Statistically significant differences (p = 0.003) were only shown for the pixels count in the AbH muscle. The rest of outcome measurements did not show any statistically significant difference (p > 0.05). Therefore, B-mode ultrasound imaging Image J software differences for the pixels count reduction were shown in the AbH muscle between hemiparetic and contralateral feet from poststroke patients. Further studies are necessary in order to apply our findings as potential biomarkers during the stroke disease course.

Mangrove spectra changes induced by oil spills monitored by image differencing of normalised indices: Tools to assist delimitation of impacted areas

The delimitation of environmental impacts in estuaries caused by oil spills is a dynamic process. Delimitation of the impacted area based on the immediate adverse oil effects neglects responses that can manifest long after the spill has occurred. This study monitored two Brazilian estuaries damaged by oil spills, searching for their effect on mangrove vegetation. The spills spread large amounts of oil into the estuarine waters of Guanabara and Paranaguá Bays, affecting the mangrove and other environmental compartments. The mangrove regions in these bays were monitored under NDVI (Normalised Difference Vegetation Index) and NDII (Normalised Difference Infrared Index), using different epoch Landsat 5TM and 7ETM+ images contemporaneous to the spills, radiometrically corrected and coregistered. Differencing images (ΔNDVI and ΔNDII) were used to assess response to the spill. Differencing images identified areas where vegetation signals had decreased or increased. In order to track seasonal mangrove spectra variations, Reference areas were chosen in each studied bay. Mean pixel value (µ) and standard deviation (σ) were calculated from differencing images of said Reference areas and defined threshold values were applied to the Monitored areas. Differencing images of Monitored areas presenting pixel values below the lower threshold (µ − 3σ) suggested a significant decrease in the normalised index and oil-impacted mangrove vegetation, whereas pixel values above the upper threshold (µ + 3σ) suggested a significant increase in the normalised index and recovery of impacted mangrove. Results showed that 4.95 ha of Monitored areas 1 and 2 in Guanabara Bay presented a significant decrease in NDVI 40 days after the spill; 10.9% of which also presented a significant decrease in NDII. An area of 9 ha of Monitored areas 1 and 2 in Paranaguá Bay presented a significant decrease in NDVI 20 days after the spill; no area presented such signals before the spill and just 0.9 ha still presented pixel values below the lower threshold 7 months after the spill. An area of 8.64 ha of Monitored area 3 in Paranaguá Bay presented a significant decrease in NDVI 20 days after the spill, 3.24 ha of which showed significant increase in NDVI after 7 months, compatible with vegetation recovery. Artifact signals induced by tides were discussed. The results point to areas not considered in the official environmental assessments currently available, thus enabling an enlargement of the original impacted area delimitations. The methodology used is suitable for initial and rapid remote assessment, with the aim of defining hotspots for fieldwork examinations, such as those required during environmental forensic examinations.

Fusion of Three Band Magnetic Resonance Images Using Sharp Frequency Localized Contourlet Transform

Background: T1, T2 and PD weighted images are the three bands of magnetic resonance image and they provide complementary information of the structure of the part being imaged. It is more useful for diagnosis and analysis if they are fused into MRI triplet. Discussion: This paper proposes a novel fusion method using Selective Frequency Localization Contourlet Transform to combine these three bands into one. Conclusion: From the qualitative and quantitative evaluation using average pixel intensity, standard deviation, mutual information and edge information based objective criteria, the fused image is found to be more informative. Keywords: Magnetic resonance images, cycle spinning, contourlet transform, spatial frequency, sum modified laplacian, fusion method.