Use of digital image analysis combined with fractal theory to determine particle morphology and surface texture of quartz sands

The particle morphology and surface texture play a major role in influencing mechanical and hydraulic behaviors of sandy soils. This paper presents the use of digital image analysis combined with fractal theory as a tool to quantify the particle morphology and surface texture of two types of quartz sands widely used in the region of Vitória, Espírito Santo, southeast of Brazil. The two investigated sands are sampled from different locations. The purpose of this paper is to present a simple, straightforward,reliable and reproducible methodology that can identify representative sandy soil texture parameters.The test results of the soil samples of the two sands separated by sieving into six size fractions are presented and discussed. The main advantages of the adopted methodology are its simplicity, reliability of the results, and relatively low cost. The results show that sands from the coastal spit(BS) have a greater degree of roundness and a smoother surface texture than river sands(RS). The values obtained in the test are statistically analyzed, and again it is confirmed that the BS sand has a slightly greater degree of sphericity than that of the RS sand. Moreover, the RS sand with rough surface texture has larger specific surface area values than the similar BS sand, which agree with the obtained roughness fractal dimensions. The consistent experimental results demonstrate that image analysis combined with fractal theory is an accurate and efficient method to quantify the differences in particle morphology and surface texture of quartz sands.

Mouse Karyotype Obtained by Combining DAPI Staining with Image Analysis

In this study, mitotic metaphase chromosomes in mouse were identified by a new chromosome fluorescence banding technique combining DAPI staining with image analysis. Clear 4＇, 6-diamidino-2-phenylindole （DAPI） multiple bands like （J-hands could be produced in mouse. The Meta- Morph software was then used to generate linescans of pixel intensity for the banded chromosomes from short arm to long arm. These linescans were sufficient not only to identify each individual chromosome but also analyze the physical sites of bands in chromosome. Based on the results, the clear and accurate karyotype of mouse metaphase chromosomes was established. The technique is therefore considered to he a new method for cytological studies of mouse.

Pelage color of red bats Lasiurus borealis varies with body size:An image analysis of museum specimens

Mammalian pelage color can vary among individuals of many species, although this intraspecific variation is oftenoverlooked by researchers, perhaps because of its sometimes subtle nature and difficulty in assessing it quantitatively. Thus, suchvariation is rarely studied in mammals, and this is especially true within the order Chiroptera, where there has been very little empiricalresearch. We examined museum specimens of red bats (Lasiurus borealis, family Vespertilionidae) from Georgia, USA, todetermine the extent of sexual dimorphism in pelage color and to explore possible associations between body size and pelagecolor. We photographed 54 specimens under uniform lighting, and used an image analysis program to measure pelage hue on theuropatagium region, which is fully furred in members of the genus Lasiurus. Statistical analyses of pelage hue scores showedmales had significantly redder pelage than females when considered alone, but when examined together with effects of body sizeand collection year, sex was not significant, and collection year and body size were. More recent specimens tended to be less redthan older specimens, which might indicate a wearing of the buffy tips of hairs from older specimens, and smaller bats of bothsexes tended to be more red. These interesting findings are encouraging and we suggest that future explorations into intraspecificvariation in pelage color of bats using this or similar approaches are warranted to clarify the significance of the patterns. Thisstudy also demonstrated that care must be taken in analyses of mammalian pelage color from older museum skins, or at least thatresearchers must take into account the age of the specimens .

Pre-training transformer with dual-branch context content module for table detection in document images

Background Document images such as statistical reports and scientific journals are widely used in information technology.Accurate detection of table areas in document images is an essential prerequisite for tasks such as information extraction.However,because of the diversity in the shapes and sizes of tables,existing table detection methods adapted from general object detection algorithms,have not yet achieved satisfactory results.Incorrect detection results might lead to the loss of critical information.Methods Therefore,we propose a novel end-to-end trainable deep network combined with a self-supervised pretraining transformer for feature extraction to minimize incorrect detections.To better deal with table areas of different shapes and sizes,we added a dualbranch context content attention module(DCCAM)to high-dimensional features to extract context content information,thereby enhancing the network's ability to learn shape features.For feature fusion at different scales,we replaced the original 3×3 convolution with a multilayer residual module,which contains enhanced gradient flow information to improve the feature representation and extraction capability.Results We evaluated our method on public document datasets and compared it with previous methods,which achieved state-of-the-art results in terms of evaluation metrics such as recall and F1-score.https://github.com/Yong Z-Lee/TD-DCCAM.

Determination of the Early Time of Death by Computerized Image Analysis of DNA Degradation: Which Is the Best Quantitative Indicator of DNA Degradation?

This study evaluated the correlation between DNA degradation of the splenic lymphocytes and the early time of death, examined the early time of death by computerized image analysis technique （CIAT） and identified the best parameter that quantitatively reflects the DNA degradation. The spleen tissues from 34 SD rats were collected, subjected to cell smearing every 2 h within the first 36 h after death, stained by Feulgen-Van＇s staining, three indices reflecting DNA content in splenic lymphocytes, including integral optical density （IOD）, average optical density （AOD）, average gray scale （AG） were measured by the image analysis. Our results showed that IOD and AOD decreased and AG increased over time within the first 36 h. A stepwise linear regression analysis showed that only AG was fitted. A correlation between the postmortem interval （PMI） and AG was identified and the corresponding regression equation was obtained. Our study suggests that CIAT is a useful and promising tool for the estimation of early PMI with good objectivity and reproducibility, and AG is a more effective and better quantitative indicator for the estimation of PMI within the first 36 h after death in rats.

Assessment and Visualization of Ki67 Heterogeneity in Breast Cancers through Digital Image Analysis

The Ki67 index (KI) is a standard clinical marker for tumor proliferation;however, its application is hindered by intratumoral heterogeneity. In this study, we used digital image analysis to comprehensively analyze Ki67 heterogeneity and distribution patterns in breast carcinoma. Using Smart Pathology software, we digitized and analyzed 42 excised breast carcinoma Ki67 slides. Boxplots, histograms, and heat maps were generated to illustrate the KI distribution. We found that 30% of cases (13/42) exhibited discrepancies between global and hotspot KI when using a 14% KI threshold for classification. Patients with higher global or hotspot KI values displayed greater heterogenicity. Ki67 distribution patterns were categorized as randomly distributed (52%, 22/42), peripheral (43%, 18/42), and centered (5%, 2/42). Our sampling simulator indicated analyzing more than 10 high-power fields was typically required to accurately estimate global KI, with sampling size being correlated with heterogeneity. In conclusion, using digital image analysis in whole-slide images allows for comprehensive Ki67 profile assessment, shedding light on heterogeneity and distribution patterns. This spatial information can facilitate KI surveys of breast cancer and other malignancies.

Collagen proportionate area of liver tissue determined by digital image analysis in patients with HBV-related decompensated cirrhosis

BACKGROUND: The accurate assessment of the degree of hepatic fibrosis plays a critical role in guiding the diagnosis, treatment and prognostic assessment of chronic liver diseases. Liver biopsy is currently the most reliable method to evaluate the severity of hepatic fibrosis. However, liver biopsy is an invasive procedure associated with morbidity and mortality, and has several limitations in patients with decompensated cirrhosis. There is no report on the collagen proportionate area (CPA) of liver tissue in the decompensated stage of cirrhosis. This study aimed to determine the CPA of resected liver tissue samples from patients with HBV-related decompensated cirrhosis using digital image analysis, and to analyze the relationship between the CPA and liver functional reserve. METHODS: Fifty-three resected liver tissue samples from liver transplant patients with chronic hepatitis B-induced decompensated cirrhosis were stained with Masson’s trichrome, and the CPA in these samples was quantitatively determined using digital image analysis. The values of relevant liver function just before liver transplantation, the CPA in liver tissue, and their correlation were analyzed. RESULTS: The mean CPA at the decompensated stage of cirrhosis was 35.93±14.42% (11.24%-63.41%). The correlation coefficients of the CPA with a model for end-stage liver disease score, serum total bilirubin and international standard ratio of prothrombin B were 0.553, 0.519 and 0.533, respectively (P<0.001). With increasing CPA values, the three indices reflecting liver functional reserve also changed significantly.CONCLUSIONS: The degree of fibrosis may be correlated with the functional reserve. With the advancement of fibrosis, the liver functional reserve is attenuated accordingly.

An investigation on dissolution kinetics of single sodium carbonate particle with image analysis method

Dissolution kinetics of sodium carbonate is investigated with the image analysis method at the approach of single particle.The dissolution experiments are carried out in an aqueous solution under a series of controlled temperature and p H.The selected sodium carbonate particles are all spherical with the same mass and diameter.The dissolution process is quantified with the measurement of particle diameter from dissolution images.The concentration of dissolved sodium carbonate in solvent is calculated with the measured diameter of particle.Both surface reaction model and mass transport model are implemented to determine the dissolution mechanism and quantify the dissolution rate constant at each experimental condition.According to the fitting results with both two models,it is clarified that the dissolution process at the increasing temperature is controlled by the mass transport of dissolved sodium carbonate travelling from particle surface into solvent.The dissolution process at the increasing pH is controlled by the chemical reaction on particle surface.Furthermore,the dissolution rate constant for each single spherical sodium carbonate particle is quantified and the results show that the dissolution rate constant of single spherical sodium carbonate increases significantly with the rising of temperature,but decreases with the increasing of pH conversely.

DIGITAL IMAGE ANALYSIS OF PHASE STRUCTURE IN THE BLEND OF POLY(BUTYLENE TEREPHTHALATE-COCAPROLACTONE) WITH POLYCARBONATE

The digital image processing technique was used for the extraction of physical information from the temporal image of phase structure in the process of phase separation in the blend of poly (butylene terephthalate-co-caprolactone )with polycarbonate. The power spectrum images of the two-dimensional Fourier transformation (2DFT) of the temporal image of phase structure reflect the change of the phase size with time.

Image cytometric DNA analysis of mucosal biopsies in patients with primary achalasia

AIM： To determine DNA aneuploidy in mucosal biopsies of achalasia patients for subsequent rapid diagnosis. METHODS： Biopsies from the middle third of the esophagus were obtained in 15 patients with achalasia. Immunohistochemical staining was carried out with monoclonal antibodies MIB-1 for Ki67 and PAb 1801 for p53, in addition to the conventional histologic examination for dysplasia. Nuclei of fresh biopsy material were enzymatically and mechanically isolated, and the DNA content was determined with image cytometry after Feulgen staining. DNA grading of malignancy was assessed according to Boecking to determine the variability of DNA values noted around the normal diploid peak. Further indices measured included the aneuploid rate, and the 5c-, 7c- and 9c-exceeding rate. RESULTS： The histological examination did not demonstrate dysplasia; while MIB-1 （basal） showed a positive reaction in 8/15 achalasia specimens, p53 was negative in all specimens. Image cytometric DNA analysis detected aneuploidy in 4/15 （26.7%） specimens. Samples from 15 patients with squamous cell carcinoma as well as specimens obtained exclusively 2 cm proximal to the tumor served as reference tests. All carcinomas （15/15） as well as 9 of the peritumoral samples （9/15） were aneuploid. The comparison of biopsies from achalasia patients with peritumoral and carcinoma specimens revealed statistically significant differences regarding the aneuploid rate （diploid： P 〈 0.0001; tetraploid： P = 0.001）, grading of malignancy according to Boecking （P 〈 0.0001） and the 5c- （P 〈 0.0001）, 7c-（P 〈 0.0001）, and 9c- （P = 0.0001） exceeding rate with progredient DNA alterations in the respective order. CONCLUSION： The finding that DNA aneuploidy was identified by image cytometry in esophageal specimens of patients with achalasia, which may be due to specific chromosomal alterations presenting as precancerous lesions in 27% of patients, leads us to conclude that image cytometry represents a valuable screening tool.

Enhanced Tunicate Swarm Optimization with Transfer Learning Enabled Medical Image Analysis System

Medical image analysis is an active research topic,with thousands of studies published in the past few years.Transfer learning(TL)including convolutional neural networks(CNNs)focused to enhance efficiency on an innovative task using the knowledge of the same tasks learnt in advance.It has played a major role in medical image analysis since it solves the data scarcity issue along with that it saves hardware resources and time.This study develops an EnhancedTunicate SwarmOptimization withTransfer Learning EnabledMedical Image Analysis System(ETSOTL-MIAS).The goal of the ETSOTL-MIAS technique lies in the identification and classification of diseases through medical imaging.The ETSOTL-MIAS technique involves the Chan Vese segmentation technique to identify the affected regions in the medical image.For feature extraction purposes,the ETSOTL-MIAS technique designs a modified DarkNet-53 model.To avoid the manual hyperparameter adjustment process,the ETSOTLMIAS technique exploits the ETSO algorithm,showing the novelty of the work.Finally,the classification of medical images takes place by random forest(RF)classifier.The performance validation of the ETSOTL-MIAS technique is tested on a benchmark medical image database.The extensive experimental analysis showed the promising performance of the ETSOTL-MIAS technique under different measures.

Political Optimizer with Deep Learning-Enabled Tongue Color Image Analysis Model

Biomedical image processing is widely utilized for disease detection and classification of biomedical images.Tongue color image analysis is an effective and non-invasive tool for carrying out secondary detection at anytime and anywhere.For removing the qualitative aspect,tongue images are quantitatively inspected,proposing a novel disease classification model in an automated way is preferable.This article introduces a novel political optimizer with deep learning enabled tongue color image analysis(PODL-TCIA)technique.The presented PODL-TCIA model purposes to detect the occurrence of the disease by examining the color of the tongue.To attain this,the PODL-TCIA model initially performs image pre-processing to enhance medical image quality.Followed by,Inception with ResNet-v2 model is employed for feature extraction.Besides,political optimizer(PO)with twin support vector machine(TSVM)model is exploited for image classification process,shows the novelty of the work.The design of PO algorithm assists in the optimal parameter selection of the TSVM model.For ensuring the enhanced outcomes of the PODL-TCIA model,a wide-ranging experimental analysis was applied and the outcomes reported the betterment of the PODL-TCIA model over the recent approaches.

3D characterization and analysis of pore structure of packed ore particle beds based on computed tomography images

Methods and procedures of three-dimensional （3D） characterization of the pore structure features in the packed ore particle bed are focused. X-ray computed tomography was applied to deriving the cross-sectional images of specimens with single particle size of 1-2, 2-3, 3-4, 4-5, 5-6, 6-7, 7-8, 8-9, 9-10 ram. Based on the in-house developed 3D image analysis programs using Matlab, the volume porosity, pore size distribution and degree of connectivity were calculated and analyzed in detail. The results indicate that the volume porosity, the mean diameter of pores and the effective pore size （d50） increase with the increasing of particle size. Lognormal distribution or Gauss distribution is mostly suitable to model the pore size distribution. The degree of connectivity investigated on the basis of cluster-labeling algorithm also increases with increasing the particle size approximately.

Use of high-resolution X-ray computed tomography and 3D image analysis to quantify mineral dissemination and pore space in oxide copper ore particles

Mineral dissemination and pore space distribution in ore particles are important features that influence heap leaching performance. To quantify the mineral dissemination and pore space distribution of an ore particle, a cylindrical copper oxide ore sample (I center dot 4.6 mm x 5.6 mm) was scanned using high-resolution X-ray computed tomography (HRXCT), a nondestructive imaging technology, at a spatial resolution of 4.85 mu m. Combined with three-dimensional (3D) image analysis techniques, the main mineral phases and pore space were segmented and the volume fraction of each phase was calculated. In addition, the mass fraction of each mineral phase was estimated and the result was validated with that obtained using traditional techniques. Furthermore, the pore phase features, including the pore size distribution, pore surface area, pore fractal dimension, pore centerline, and the pore connectivity, were investigated quantitatively. The pore space analysis results indicate that the pore size distribution closely fits a log-normal distribution and that the pore space morphology is complicated, with a large surface area and low connectivity. This study demonstrates that the combination of HRXCT and 3D image analysis is an effective tool for acquiring 3D mineralogical and pore structural data.

Image Analysis on Detachment Process of Dust Cake on Ceramic Candle Filter

Based on the analysis of high-speed video images, the detachment behavior of dust cake from the ceramic candle filter surface during pulse cleaning process is investigated. The influences of the dust cake loading,the reservoir pressure, and the filtration velocity on the cleaning effectiveness are analyzed. Experimental results show that there exists an optimum dust cake thickness for pulse-cleaning process. For thin dust cake, the patchy cleaning exists and the cleaning efficiency is low; if the dust cake is too thick, the pressure drop across the dust cake becomes higher and a higher reservoir pressure may be needed. At the same time there also exists an optimum reservoir pressure for a given filtration condition.

Review of Remotely Sensed Imagery Classification Patterns Based on Object-oriented Image Analysis

With the wide use of high-resolution remotely sensed imagery, the object-oriented remotely sensed informa- tion classification pattern has been intensively studied. Starting with the definition of object-oriented remotely sensed information classification pattern and a literature review of related research progress, this paper sums up 4 developing phases of object-oriented classification pattern during the past 20 years. Then, we discuss the three aspects of method- ology in detail, namely remotely sensed imagery segmentation, feature analysis and feature selection, and classification rule generation, through comparing them with remotely sensed information classification method based on per-pixel. At last, this paper presents several points that need to be paid attention to in the future studies on object-oriented RS in- formation classification pattern: 1) developing robust and highly effective image segmentation algorithm for multi-spectral RS imagery; 2) improving the feature-set including edge, spatial-adjacent and temporal characteristics; 3) discussing the classification rule generation classifier based on the decision tree; 4) presenting evaluation methods for classification result by object-oriented classification pattern.

Fluorescence Microscopic Image Analysis of Nucleic Acids Based on The Capillary Flow Directed Assembly Ring of Neutral Red-nucleic Acid Supramolecular Complexes

It is critical to establish a direct and precise method with a high sensitivity and selectivity in analytical chemistry. In this research, making use of a well known phenomenon of capillary flow, we have proposed an image analysis method of nucleic acids at the price of a small amount of sample. When a droplet of the supramolecular complex solution, formed by neutral red and nucleic acids(NA) under an approximate neutral condition, was placed on the hydrophobic surface of dimethyl dichlorosilane pretreated glass slides, and it was evaporated, the supramolecular complex exhibited the periphery of the droplet due to the capillary effect, and accumulated there to form a red capillary flow directed assembly ring(CFDAR). A typical CFDAR has an outer diameter of (2 r ) about 1.18 mm and a ring width(2 δ ) of about 41 μm. Depending on the experimental conditions, a variety of CFDAR can be assembled. The experimental results are in agreement with our former theoretical discussion. It was found that when a droplet volume is 0.1 μL, the fluorescence intensity of the CFDAR formed by the NR NA is in proportion to the content of calf thymus DNA in the range of 0-0.28 ng, fish sperm DNA of 0-0.24 ng and yeast RNA of 0-0.16 ng with the limit of detection(3 σ ) of 1 7, 1.4 and 0.9 pg, respectively for the three nucleic acids.

Multi-Modality Medical Image Fusion Based on Wavelet Analysis and Quality Evaluation

Multi-modality medical image fusion has more and more important applications in medical image analysis and understanding. In this paper, we develop and apply a multi-resolution method based on wavelet pyramid to fuse medical images from different modalities such as PET-MRI and CT-MRI. In particular, we evaluate the different fusion results when applying different selection rules and obtain optimum combination of fusion parameters.

Application of Image Analysis Based on SEM and Chemical Mapping on PC Mortars under Sulfate Attack

The degradation mechanisms of cementitious materials exposed to sulfate solutions have been controversial, despite considerable research. In this paper, two methodologies of image analysis based on scanning electron microscope and chemical mapping are used to analyse Portland cement mortars exposed to sodium sulfate solution. The effects of sulfate concentration in solution and water to cement ratio of mortar, which are considered as the most sensitive factors to sulfate attack, are investigated respectively by comparing the macro expansion with microstructure analysis. It is found that the sulfate concentration in pore solution, expressed as sulfate content in C-S-H, plays a critical role on the supersaturation with respect to ettringite and so on the expansion force generated.

Research on image sentiment analysis technology based on sparse representation

Many methods based on deep learning have achieved amazing results in image sentiment analysis.However,these existing methods usually pursue high accuracy,ignoring the effect on model training efficiency.Considering that when faced with large-scale sentiment analysis tasks,the high accuracy rate often requires long experimental time.In view of the weakness,a method that can greatly improve experimental efficiency with only small fluctuations in model accuracy is proposed,and singular value decomposition(SVD)is used to find the sparse feature of the image,which are sparse vectors with strong discriminativeness and effectively reduce redundant information;The authors propose the Fast Dictionary Learning algorithm(FDL),which can combine neural network with sparse representation.This method is based on K-Singular Value Decomposition,and through iteration,it can effectively reduce the calculation time and greatly improve the training efficiency in the case of small fluctuation of accuracy.Moreover,the effectiveness of the proposed method is evaluated on the FER2013 dataset.By adding singular value decomposition,the accuracy of the test suite increased by 0.53%,and the total experiment time was shortened by 8.2%;Fast Dictionary Learning shortened the total experiment time by 36.3%.