Texture Analysis of The Microstructure of Internal Curing Concrete Based On Image Recognition Technology

Mechanical properties of internal curing concrete are greatly affected by its physical properties such as water content, cementing material content, porosity, and saturation. At the micro level, such impact is finally reflected in the surface texture of its materials. In this study, the image recognition technology was used to find that the internal curing concrete samples have significant micromorphology and texture features. A texture parameter–strength model was established based on the relationship between Tamura texture parameters, gray level co-occurrence matrix (GLCM) texture parameters, and the mechanical strength. Due to the characteristics of materials and the sensitivity of parameters, not all Tamura and GLCM texture parameters can effectively characterize the texture features of internal curing concrete materials. In terms of the Tamura texture, coarseness, regularity, and directionality are effective parameters to predict the compressive strength of the internal curing concrete. In terms of the GLCM texture, energy, correlation, entropy, and contrast are effective parameters to predict the compressive strength of the internal curing concrete. Correlations between each texture parameter and compressive strength follow different laws.

18F-FDG texture analysis predicts the pathological Fuhrman nuclear grade of clear cell renal cell carcinoma

Purpose This article analyzes the image heterogeneity of clear cell renal cell carcinoma (ccRCC) based on positron emission tomography (PET) and positron emission tomography-computed tomography (PET/CT) texture parameters, and provides a new objective quantitative parameter for predicting pathological Fuhrman nuclear grading before surgery. Methods A retrospective analysis was performed on preoperative PET/CT images of 49 patients whose surgical pathology was ccRCC, 27 of whom were low grade (Fuhrman I/II) and 22 of whom were high grade (Fuhrman III/IV). Radiological parameters and standard uptake value (SUV) indicators on PET and computed tomography (CT) images were extracted by using the LIFEx software package. The discriminative ability of each texture parameter was evaluated through receiver operating curve (ROC). Binary logistic regression analysis was used to screen the texture parameters with distinguishing and diagnostic capabilities and whose area under curve (AUC) > 0.5. DeLong's test was used to compare the AUCs of PET texture parameter model and PET/CT texture parameter model with traditional maximum standardized uptake value (SUVmax) model and the ratio of tumor SUVmax to liver SUVmean (SUL)model. In addition, the models with the larger AUCs among the SUV models and texture models were prospectively internally verified. Results In the ROC curve analysis, the AUCs of SUVmax model, SUL model, PET texture parameter model, and PET/CT texture parameter model were 0.803, 0.819, 0.873, and 0.926, respectively. The prediction ability of PET texture parameter model or PET/CT texture parameter model was significantly better than SUVmax model (P = 0.017, P = 0.02), but it was not better than SUL model (P = 0.269, P = 0.053). In the prospective validation cohort, both the SUL model and the PET/CT texture parameter model had good predictive ability, and the AUCs of them were 0.727 and 0.792, respectively. Conclusion PET and PET/CT texture parameter models can improve the prediction ability of ccRCC Fuhrman nuclear grade; SUL model may be the more accurate and easiest way to predict ccRCC Fuhrman nuclear grade. Graphic abstract

DIPG-37. PREDICTING OUTCOME IN CHILDHOOD DIFFUSE MIDLINE GLIOMAS USING MAGNETIC RESONANCE IMAGING BASED TEXTURE ANALYSIS

BACKGROUND Diffuse midline gliomas (DMG) are aggressive brain tumours with 10% overall survival (OS) at 18 months. Predicting OS will help refine treatment strategy in this patient group. MRI based texture analysis (MRTA) is a novel technique that provides objective information about spatial arrangement of MRI signal intensity and has potential as an imaging biomarker. OBJECTIVES: To investigate MRTA in predicting OS in childhood DMG. METHODS Retrospective study of patients diagnosed with DMG, based on radiological features, treated at our institution 2007–2017. MRIs were accomplished at diagnosis and 6 weeks after radiotherapy (54Gy in 30 fractions). MRTA, performed using TexRAD software, on T2W sequence and Apparent Diffusion Coefficient (ADC) maps encapsulated tumour in the largest single axial plane. MRTA comprised filtration-histogram technique using statistical and histogram metrics for quantification of texture. Kaplan-Meier analysis determined association of MRI texture parameters with OS. RESULTS 32 children 2–14 years (median 7 years) were included. MRTA was undertaken on T2W (n=32) and ADC (n=22). MRTA on T2W was better at prognosticating than on ADC maps. Children with homogenous tumour texture, at medium scale on baseline T2W MRI, had worse prognosis (mean p=0.0098, SD p=0.0115, entropy p=0.0422, mean of positive pixels (MPP) p=0.0051, kurtosis p=0.0374). MPP was the most significant texture parameter. Median survival in this group as identified by MRTA (medium texture, MPP) was 7.5 months versus 17.5 months. CONCLUSIONS DMG with more homogeneous texture on diagnostic MRI is associated with worse prognosis. MPP texture parameter is the most predictive of OS in childhood DMG.

High pressure and thermal processing on the quality of zucchini slices

In response to the market demand for low processed vegetables, high-pressure treatments (400,600 MPa; 1,5 min) were applied on zucchini slices and compared to a traditional blanching treatment. Histological observations, texture and color analysis, pectinmethylesterase (PME) and antioxidant (DPPH) activities were measured and compared to untreated samples. The histological observations revealed that the longer high-pressure treatments (5 min) led to more extended cell lysis and dehydration than the shorter ones (1 min) and blanching. High-pressure treatments resulted less effective than blanching on PME inactivation, with the best results obtained at 400 MPa for 1 min. Comparable texture parameters were observed for high-pressured and blanched samples. The negative correlation found between PME activity and the texture parameter ‘distance of the first peak force’ revealed an effect of PME on the texture recovery after treatments. High pressure led to a general browning of zucchini parenchyma and to DPPH drop. The correlations found between DPPH and color suggest the common nature of the phenomena. The influence of pressure and time on the studied parameters was revealed by two-way ANOVA. Principal component analysis clustered together the four high-pressure-treated samples, being clearly divided by blanched and untreated ones.

Comparing samples from the G distribution using a geodesic distance

© 2019, Sociedad de Estadística e Investigación Operativa. The G distribution is widely used for monopolarized SAR image modeling because it can characterize regions with different degrees of texture accurately. It is indexed by three parameters: the number of looks (which can be estimated for the whole image), a scale parameter and a texture parameter. This paper presents a new proposal for comparing samples from the G distribution using a geodesic distance (GD) as a measure of dissimilarity between models. The objective is quantifying the difference between pairs of samples from SAR data using both local parameters (scale and texture) of the G distribution. We propose three tests based on the GD which combine the tests presented in Naranjo-Torres et al. (IEEE J Sel Top Appl Earth Obs Remote Sens 10(3):987–997, 2017), and we estimate their probability distributions using permutation methods.

Comparing samples from the G distribution using a geodesic distance

© 2019, Sociedad de Estadística e Investigación Operativa. The G distribution is widely used for monopolarized SAR image modeling because it can characterize regions with different degrees of texture accurately. It is indexed by three parameters: the number of looks (which can be estimated for the whole image), a scale parameter and a texture parameter. This paper presents a new proposal for comparing samples from the G distribution using a geodesic distance (GD) as a measure of dissimilarity between models. The objective is quantifying the difference between pairs of samples from SAR data using both local parameters (scale and texture) of the G distribution. We propose three tests based on the GD which combine the tests presented in Naranjo-Torres et al. (IEEE J Sel Top Appl Earth Obs Remote Sens 10(3):987–997, 2017), and we estimate their probability distributions using permutation methods.

Efek penambahan oats pada formulasi cookies gandum dilihat dari karakteristik fisik dan sensorinya

This research aims to determine the effect of oats addition in wheat cookies formulation seen from physical and sensory characteristics. Six formulations used in this research consist of wheat flour and oats mixture namely Control (100%:0%), Formulation 1 (80%:20%), Formulation 2 (60%:40%), Formulation 3 (40%:60%), Formulation 4 (20%:80%), and Formulation 5 (0%:100%). Based on analysis of variance result at α = 5%, there was a significant difference in the value of hardness and work from control and all variation of cookies’ formulation. It was also found that the decreasing composition of wheat flour and increasing composition of oats caused a decrease in the value of hardness and work. The addition of oats in the formulation of wheat cookies increases the level of brightness (L), decreases the value of a* (red tone), and increases the value of b* (yellow tone) of cookies. From sensory evaluation, compared to controls, the addition of oats in the formulation increased the acceptance rating for color parameter for all formulation, taste parameter for Formulation 2 until 5, and overall parameter for Formulation 2 and 3, while for the texture parameter, the addition of oats did not provide an increased in the acceptance rating.