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Yongzhen Zhang, Yanbo Hui, Ying Zhou, Juanjuan Liu, Ju Gao, Xiaoliang Wang, Baiwei Wang, Mengqi Xie and Haonan Hou
Moldy corn produces aflatoxin and gibberellin, which can have adverse effects on human health if consumed. Mold is a significant factor that affects the safe storage of corn. If not detected and controlled in a timely manner, it will result in substantia...
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Xueping Song, Shuyu Zhang, Jianming Yang and Jicun Zhang
Many security detectors do not have the ability to output individual luggage package images and are not compatible with deep learning algorithms. In this paper, a luggage package extraction of X-ray images based on the ES-MBD (Edge Sensitive Multi-channe...
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Eldred Lee, Kevin D. Larkin, Xin Yue, Zhehui Wang, Eric R. Fossum and Jifeng Liu
This article experimentally investigates the inception of an innovative hard X-ray photon energy attenuation layer (PAL) to advance high-energy X-ray detection (20?50 keV). A bi-layer design with a thin film high-Z PAL on the top and Si image sensor on t...
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Frank Liebold, Franz Wagner, Josiane Giese, Szymon Grzesiak, Christoph de Sousa, Birgit Beckmann, Matthias Pahn, Steffen Marx, Manfred Curbach and Hans-Gerd Maas
Carbon-reinforced concrete (CRC) is increasingly utilized in construction, due to its unique properties, such as corrosion resistance, high-tensile strength, and durability. Understanding its behavior under different loads is crucial to ensuring its safe...
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Clara Freijo, Joaquin L. Herraiz, Fernando Arias-Valcayo, Paula Ibáñez, Gabriela Moreno, Amaia Villa-Abaunza and José Manuel Udías
Chest X-rays (CXRs) represent the first tool globally employed to detect cardiopulmonary pathologies. These acquisitions are highly affected by scattered photons due to the large field of view required. Scatter in CXRs introduces background in the images...
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Qingji Guan, Qinrun Chen and Yaping Huang
Chest X-ray image classification suffers from the high inter-similarity in appearance that is vulnerable to noisy labels. The data-dependent and heteroscedastic characteristic label noise make chest X-ray image classification more challenging. To address...
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Daniele Passaretti, Mukesh Ghosh, Shiras Abdurahman, Micaela Lambru Egito and Thilo Pionteck
In computed tomography imaging, the computationally intensive tasks are the pre-processing of 2D detector data to generate total attenuation or line integral projections and the reconstruction of the 3D volume from the projections. This paper proposes th...
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Wen-Tien Hsiao, Hsin-Hon Lin and Lu-Han Lai
Digital radiography is currently the main method of medical imaging diagnosis. It also has a wide range of applications across different fields. This study used radiation to conduct non-destructive visual imaging, and further established a quantitative a...
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Wen-Tien Hsiao, Wen-Chi Kuo, Hsin-Hon Lin and Lu-Han Lai
Digital radiography (DR) is a mature technology and has been broadly used in medical diagnosis. Currently, it?s also used for fruit quality inspection in the market. This purpose of the study is to conduct non-destructive experiments for visual compariso...
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Eldred Lee, Kaitlin M. Anagnost, Zhehui Wang, Michael R. James, Eric R. Fossum and Jifeng Liu
High-energy (>20 keV) X-ray photon detection at high quantum yield, high spatial resolution, and short response time has long been an important area of study in physics. Scintillation is a prevalent method but limited in various ways. Directly detecting ...
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Shaw-Hwa Lo and Yiqiao Yin
The field of explainable artificial intelligence (XAI) aims to build explainable and interpretable machine learning (or deep learning) methods without sacrificing prediction performance. Convolutional neural networks (CNNs) have been successful in making...
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Lourdes Duran-Lopez, Juan Pedro Dominguez-Morales, Jesús Corral-Jaime, Saturnino Vicente-Diaz and Alejandro Linares-Barranco
This work could be used to aid radiologists in the screening process, contributing to the fight against COVID-19.
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Chichun Hu, Jiexian Ma and M. Emin Kutay
In order to perform three-dimensional digital sieving based on X-ray computed tomography images, the definition of digital sieve size (DSS) was proposed, which was defined as the minimum length of the minimum bounding squares of all possible orthographic...
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G. Raghavendra Prasad
In medical imaging, the scope of image enhancement is highly challenging. Here digital chest x ?ray image are taken in a spatial domain and enhancement of the image is done through histogram equalization method. Histogram equalization is a specific case ...
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Shoffan Saifullah and Rafal Drezewski
Accurate medical image segmentation is paramount for precise diagnosis and treatment in modern healthcare. This research presents a comprehensive study of the efficacy of particle swarm optimization (PSO) combined with histogram equalization (HE) preproc...
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Biprodip Pal, Debashis Gupta, Md. Rashed-Al-Mahfuz, Salem A. Alyami and Mohammad Ali Moni
The COVID-19 pandemic requires the rapid isolation of infected patients. Thus, high-sensitivity radiology images could be a key technique to diagnose patients besides the polymerase chain reaction approach. Deep learning algorithms are proposed in severa...
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Roberto Visalli, Gaetano Ortolano, Gaston Godard and Rosolino Cirrincione
Micro-Fabric Analyzer (MFA) is a new GIS-based tool for the quantitative extrapolation of rock microstructural features that takes advantage both of the characteristics of the X-ray images and the optical image features. Most of the previously developed ...
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Fadhil Khadyer Alsheikh,Dr Israa Hadi Ali
The process of detecting hidden weapons is an important process right now due to the increase in terrorist operations, so the process of building an automatic weapons detection system is an important process to reduce errors resulting from manual detecti...
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Xin Li, Yang Li, Qiang Li, Xiaozhou Zhang, Xuechen Shi, Yudong Lu, Shaoxiong Zhang and Liting Zhang
Preferential flow is widely developed in varieties of voids (such as macropores and fissures) in loess areas, affecting slope hydrology and stability and even leading to geological disasters. However, the model of seepage evolution with dynamic preferent...
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Igor Varfolomeev, Ivan Yakimchuk and Ilia Safonov
Image segmentation is a crucial step of almost any Digital Rock workflow. In this paper, we propose an approach for generation of a labelled dataset and investigate an application of three popular convolutional neural networks (CNN) architectures for seg...
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