scholarly journals Study of Structural Characteristics of Ancient Bricks With Neutron Radiography Facility at BTRR

2021 ◽  
Vol 40 (3) ◽  
pp. 141-159
Author(s):  
Robin Barman ◽  
Sudipta Saha ◽  
Md. Sayed Hossain ◽  
Anik Das ◽  
Md. Kaosar Ahmmad Rabby ◽  
...  

Neutron radiography (NR) has been applied successfully to investigate different types of building materials, rock samples, sculptures, statues or monuments for since long. The utilization of neutron imaging for non-invasive investigations of cultural heritage objects is demonstrated on the example of ancient bricks found in Mahasthangarh and Sonargaon, two key archaeological sites in Bangladesh. The visualization of the internal structure of different brick samples, by means of Neutron Radiography (NR), has been experimented using the BTRR research reactor in Bangladesh - the only neutron imaging facility available in Bangladesh for R D purposes. Manufacturing building materials have become a very good option for business in developing countries like Bangladesh. Among the non-destructive testing (NDT) techniques, neutron radiography is the most common procedure to identify light and organic materials, homogeneity, any inclusion or voids or cracks etc. inside the structure. The radiographic images in a dry condition for individual samples have been investigated. The image analysis was performed using ImageJ software and texture features were extracted using gray level co-occurrence matrix implemented by MATLAB for acquiring qualitative and quantitative information from this inspection technique at a high level of accuracy. The results obtained by neutron imaging provide the statement that the brick sample from Mahasthangarh is more homogeneous inside.

2015 ◽  
Vol 7 (2) ◽  
pp. 1428-1439
Author(s):  
Khurshed Alam ◽  
Md. Sayeedur Rahman ◽  
Md. Mostafizur Rahman ◽  
S. M. Azaharul Islam

A powerful non-destructive testing (NDT) technique is adopted to study the internal defects and elemental distribution/homogeneity and porosity of aerated brick and EPS aggregate poly brick samples. In the present study the internal defects like homogeneity, porosity, elemental distribution, EPS aggregate and aerator distributor in the test samples have been observed by the measurement of gray value/optical density of the neutron radiographic images of these samples. From this measurement it is found that the neutron intensity/optical density variation with the pixel distance of the AOI of the NR images in both expanded polystyrene (EPS) aggregate poly brick and aerated brick samples comply almost same in nature with respect to the whole AOI but individually each AOI shows different nature from one AOI to another and it confirms that the elemental distribution within a AOI is almost homogeneous. Finally it was concluded that homogeneity, elemental distribution in the EPS aggregate poly brick sample is better than that of the aerated brick sample. 


1970 ◽  
Vol 43 (2) ◽  
pp. 197-206
Author(s):  
MK Alam ◽  
MN Islam ◽  
MA Zaman

Neutron radiography (NR) technique has been adopted to study homogeneity and water absorption behavior of building materials, like double layer silver gray tiles obtained from Concord Real Estate & Building Products, Unit II, Salna, Gazipur, Dhaka, Bangladesh. Measurements of optical density differences between the film background and radiographic images of the dry/wet samples were used for investigation of the present work. The optical density was measured by using the digital optical densitometer (Model 07-424, S-23285, Victoreen Inc. USA). Large variation in optical density values of the radiographic image was observed. From this observation it shows that the rate of water absorption of the tiles increases with increase of immersion time. Through the investigation of radiographic image and subsequently analyzing the optical density we observed that distribution of the elements in the tiles are inhomogeneous. Key words: Homogeneity, Water absorption, Silver gray, Neturon radiography.DOI: 10.3329/bjsir.v43i2.963 Bangladesh J. Sci. Ind. Res. 43(2), 197-206, 2008


2014 ◽  
Vol 48 (4) ◽  
pp. 237-246
Author(s):  
MK Alam ◽  
MR Islam ◽  
S Saha ◽  
MN Islam ◽  
SM Azaharul Islam

Neutron radiography is a powerful non-destructive testing (NDT) technique for internal evaluation of materials, such as voids/cavity, cracks, homogeneity, water absorption behavior, etc. It involves attenuation of a neutron beam by an object to be radiographed and thus to make the registration of the attenuation process (as an image) on a film or video. In the present investigation neutron radiography (NR) imaging technique has been adopted to study the quality like homogeneity, porosity, water penetrating height, behavior of incremental intrusion area, initial rapid absorption (IRA) of the brick-DK sample. Thermal neutron radiography facility installed at the tangential beam port of 3MW TRIGA MARK-II reactor is used in this study. In this cases optical density or gray values of the neutron radiographic images of the sample is measured. From this measurement it is found that the contents of the sample is not uniformly distributed all over the sample which indicates the presence of large number of internal porosity, at the two edges water uptake is slightly poorer than the middle part and initial rapid absorption is very high. Water penetrating inside the sample is faster. The results obtained and conclusion made in this study can only be compared to the properties of bricks produced under similar conditions with similar raw materials. DOI: http://dx.doi.org/10.3329/bjsir.v48i4.18273 Bangladesh J. Sci. Ind. Res. 48(4), 237-246, 2013


Author(s):  
Weiguo Cao ◽  
Marc J. Pomeroy ◽  
Yongfeng Gao ◽  
Matthew A. Barish ◽  
Almas F. Abbasi ◽  
...  

AbstractTexture features have played an essential role in the field of medical imaging for computer-aided diagnosis. The gray-level co-occurrence matrix (GLCM)-based texture descriptor has emerged to become one of the most successful feature sets for these applications. This study aims to increase the potential of these features by introducing multi-scale analysis into the construction of GLCM texture descriptor. In this study, we first introduce a new parameter - stride, to explore the definition of GLCM. Then we propose three multi-scaling GLCM models according to its three parameters, (1) learning model by multiple displacements, (2) learning model by multiple strides (LMS), and (3) learning model by multiple angles. These models increase the texture information by introducing more texture patterns and mitigate direction sparsity and dense sampling problems presented in the traditional Haralick model. To further analyze the three parameters, we test the three models by performing classification on a dataset of 63 large polyp masses obtained from computed tomography colonoscopy consisting of 32 adenocarcinomas and 31 benign adenomas. Finally, the proposed methods are compared to several typical GLCM-texture descriptors and one deep learning model. LMS obtains the highest performance and enhances the prediction power to 0.9450 with standard deviation 0.0285 by area under the curve of receiver operating characteristics score which is a significant improvement.


2020 ◽  
Vol 43 (1) ◽  
pp. 29-45
Author(s):  
Alex Noel Joseph Raj ◽  
Ruban Nersisson ◽  
Vijayalakshmi G. V. Mahesh ◽  
Zhemin Zhuang

Nipple is a vital landmark in the breast lesion diagnosis. Although there are advanced computer-aided detection (CADe) systems for nipple detection in breast mediolateral oblique (MLO) views of mammogram images, few academic works address the coronal views of breast ultrasound (BUS) images. This paper addresses a novel CADe system to locate the Nipple Shadow Area (NSA) in ultrasound images. Here the Hu Moments and Gray-level Co-occurrence Matrix (GLCM) were calculated through an iterative sliding window for the extraction of shape and texture features. These features are then concatenated and fed into an Artificial Neural Network (ANN) to obtain probable NSA’s. Later, contour features, such as shape complexity through fractal dimension, edge distance from the periphery and contour area, were computed and passed into a Support Vector Machine (SVM) to identify the accurate NSA in each case. The coronal plane BUS dataset is built upon our own, which consists of 64 images from 13 patients. The test results show that the proposed CADe system achieves 91.99% accuracy, 97.55% specificity, 82.46% sensitivity and 88% F-score on our dataset.


2014 ◽  
Vol 668-669 ◽  
pp. 1041-1044
Author(s):  
Lin Lin Song ◽  
Qing Hu Wang ◽  
Zhi Li Pei

This paper firstly studies the texture features. We construct a gray-difference primitive co-occurrence matrix to extract texture features by combining statistical methods with structural ones. The experiment results show that the features of the gray-difference primitive co-occurrence matrix are more delicate than the traditional gray co-occurrence matrix.


BMC Cancer ◽  
2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Sihua Niu ◽  
Jianhua Huang ◽  
Jia Li ◽  
Xueling Liu ◽  
Dan Wang ◽  
...  

Abstract Background The classification of Breast Imaging Reporting and Data System 4A (BI-RADS 4A) lesions is mostly based on the personal experience of doctors and lacks specific and clear classification standards. The development of artificial intelligence (AI) provides a new method for BI-RADS categorisation. We analysed the ultrasonic morphological and texture characteristics of BI-RADS 4A benign and malignant lesions using AI, and these ultrasonic characteristics of BI-RADS 4A benign and malignant lesions were compared to examine the value of AI in the differential diagnosis of BI-RADS 4A benign and malignant lesions. Methods A total of 206 lesions of BI-RADS 4A examined using ultrasonography were analysed retrospectively, including 174 benign lesions and 32 malignant lesions. All of the lesions were contoured manually, and the ultrasonic morphological and texture features of the lesions, such as circularity, height-to-width ratio, margin spicules, margin coarseness, margin indistinctness, margin lobulation, energy, entropy, grey mean, internal calcification and angle between the long axis of the lesion and skin, were calculated using grey level gradient co-occurrence matrix analysis. Differences between benign and malignant lesions of BI-RADS 4A were analysed. Results Significant differences in margin lobulation, entropy, internal calcification and ALS were noted between the benign group and malignant group (P = 0.013, 0.045, 0.045, and 0.002, respectively). The malignant group had more margin lobulations and lower entropy compared with the benign group, and the benign group had more internal calcifications and a greater angle between the long axis of the lesion and skin compared with the malignant group. No significant differences in circularity, height-to-width ratio, margin spicules, margin coarseness, margin indistinctness, energy, and grey mean were noted between benign and malignant lesions. Conclusions Compared with the naked eye, AI can reveal more subtle differences between benign and malignant BI-RADS 4A lesions. These results remind us carefully observation of the margin and the internal echo is of great significance. With the help of morphological and texture information provided by AI, doctors can make a more accurate judgment on such atypical benign and malignant lesions.


2021 ◽  
Vol 23 (1) ◽  
pp. 11-20
Author(s):  
Xiaofei Cui ◽  
Xiaoxia Liang ◽  
Ujjwal Bharadwaj

Metallic corrosion is a big challenge affecting many sectors in a nation’s economy. Necessary corrosion prevention actions have to be taken in order to maintain the integrity of engineering assets susceptible to corrosion. This paper proposes a holistic framework to support the management of corrosion in metallic structures. It is a fully automation corrosion assessment process, with risk updated by Bayesian theory. Through analyzing the thickness data measured by non-destructive testing (NDT) techniques, the influence of corrosion on the component can be estimated using statistical methods, which will enable users to make decisions on maintenance based on quantitative information. A case study using corrosion data from a steel bridge is included to demonstrate the proposed framework. It improved the conventional corrosion analysis method by the proposed statistical approach using representative thickness data, which aims to take full use of the remaining life. This model can be adapted to a wide range of metallic structure suffering from corrosion damage.


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