A comprehensive deep learning approach to improve enchondroma detection on X-ray images by Ayhan Aydin, Caner Ozcan, Safak Aydın Simsek, Ferhat Say

“…In this study, authentic X-ray radiographs of patients were obtained following ethical approval and subjected to preprocessing. …”
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Design of a mammography X-ray image classification assistant system adapted to Chinese population by SUN Changjin, TONG Fei, WU Yi

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Efficiency in the classification of chest X-ray images through generative parallelization of the Neural Architecture Search by Felix Mejía Cajicá, John Anderson García Henao, Carlos Jaime Barrios Hernandéz, Michel Riveill

“… Explore GenNAS for chest X-ray classification in lung diseases, leveraging novel parallel training methods for enhanced accuracy and efficiency. …”
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Development and validation of a clinical prediction model for osteoporosis diagnosis by lumbosacral X-ray and radiomics by Xiaofeng Chen, Xiaofeng Chen, Dongling Cai, Dongling Cai, Hao Li, Weijun Guo, Qian Li, Qian Li, Jinjun Liang, Junxian Xie, Jincheng Liu, Zhen Xiang, Wenxuan Dong, Sihong OuYang, Zhuozheng Deng, Qipeng Wei

“…PurposeTo develop a clinical prediction model for the diagnosis of osteoporosis using lumbosacral X-ray images through radiomics analysis.MethodsA total of 272 patients who underwent dual-energy X-ray absorptiometry (DXA) and lumbosacral X-ray examinations were categorized into two groups: (1) the training set (n = 191) and (2) the validation set (n = 81). …”
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Limited-angle x-ray nano-tomography with machine-learning enabled iterative reconstruction engine by Chonghang Zhao, Mingyuan Ge, Xiaogang Yang, Yong S. Chu, Hanfei Yan

“…Notably, it also improves the reconstruction in case of sparse projections, despite the network not being specifically trained for that. This demonstrates the robustness and generality of our method of addressing commonly occurring challenges in 3D x-ray imaging applications for real-world problems.…”
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FPGA-accelerated SpeckleNN with SNL for real-time X-ray single-particle imaging by Abhilasha Dave, Cong Wang, James Russell, Ryan Herbst, Jana Thayer

“…This hardware realization transitions SpeckleNN from a prototypic model into a practical edge solution, optimized for running inference near the detector in high-throughput X-ray free-electron laser (XFEL) facilities, such as those found at the Linac Coherent Light Source (LCLS). …”
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Deep Learning Approach for Pneumonia Prediction from X-Rays using A Pretrained Densenet Model by Ahmad Zein Al Wafi, Febry Putra Rochim, Aisya Fathimah

“…The models were trained for 20 epochs using the Adam optimizer and binary cross-entropy loss function. …”
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Advanced feature fusion of radiomics and deep learning for accurate detection of wrist fractures on X-ray images by Mohamed J. Saadh, Qusay Mohammed Hussain, Rafid Jihad Albadr, Hardik Doshi, M. M. Rekha, Mayank Kundlas, Amrita Pal, Jasur Rizaev, Waam Mohammed Taher, Mariem Alwan, Mahmod Jasem Jawad, Ali M. Ali Al-Nuaimi, Bagher Farhood

“…Abstract Objective The aim of this study was to develop a hybrid diagnostic framework integrating radiomic and deep features for accurate and reproducible detection and classification of wrist fractures using X-ray images. Materials and Methods A total of 3,537 X-ray images, including 1,871 fracture and 1,666 non-fracture cases, were collected from three healthcare centers. …”
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Automatic segmentation of chest X-ray images via deep-improved various U-Net techniques by Sedat Orenc, Mehmet Sirac Ozerdem, Emrullah Acar, Musa Yilmaz

“…This study aimed to evaluate the performance of various U-Net-based deep learning architectures for chest X-ray (CXR) segmentation and identify the most effective model in terms of both accuracy and computational efficiency. …”
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Clinicians’ Agreement on Extrapulmonary Radiographic Findings in Chest X-Rays Using a Diagnostic Labelling Scheme by Lea Marie Pehrson, Dana Li, Alyas Mayar, Marco Fraccaro, Rasmus Bonnevie, Peter Jagd Sørensen, Alexander Malcom Rykkje, Tobias Thostrup Andersen, Henrik Steglich-Arnholm, Dorte Marianne Rohde Stærk, Lotte Borgwardt, Sune Darkner, Jonathan Frederik Carlsen, Michael Bachmann Nielsen, Silvia Ingala

“…These insights aid in optimizing training strategies for both clinicians and AI models.…”
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Assessment of the Local Exposure Level during Adult Chest X-Rays at the Ngaoundere Regional Hospital, Cameroon by Guiswe Gnowe, Henri Paul Ekobena Fouda, Mbo Amvene Jéremie, Takmou Pascal, Bonaventure Babinne Graobe

“…The doses delivered in the standard X-ray examinations are not sufficiently optimized and controlled. …”
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Simulating X-ray beam energy and detector signal processing of an industrial CT using implicit neural representations by Edwin Blum, Moritz Burmeister, Florian Stamer, Gisela Lanza

“… Simulating computed tomography (CT) systems offers numerous advantages, including the optimization of scan parameters, training of specialist personnel, and quantification of measurement uncertainties. …”
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Advanced AI techniques for root disease classification in dental X-rays using deep learning and metaheuristic approach by Prem Enkvetchakul, Surajet Khonjun, Rapeepan Pitakaso, Thanatkij Srichok, Peerawat Luesak, Chutchai Kaewta, Sarayut Gonwirat, Chawis Boonmee, Matus Noowattana, Thitinon Srisuwandee

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Leveraging Radiomics and Genetic Algorithms to Improve Lung Infection Diagnosis in X-Ray Images Using Machine Learning by A. Beena Godbin, S. Graceline Jasmine

“…To optimize the performance of machine learning models, the paper incorporates genetic algorithms for hyperparameter optimization. …”
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X-ray based radiomics machine learning models for predicting collapse of early-stage osteonecrosis of femoral head by Yaqing He, Yang Chen, Yusen Chen, Pingshi Li, Le Yuan, Maoxiao Ma, Yuhao Liu, Wei He, Wu Zhou, Leilei Chen

“…Abstract This study aimed to develop an X-ray radiomics model for predicting collapse of early-stage osteonecrosis of the femoral head (ONFH). …”
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Minimizing Radiation Exposure in Neonatal Intensive Care Unit: A Quality Improvement Approach on X-Ray Practices by Jae Hui Ryu, Seung Han Shin, Young Hun Choi, Ee-Kyung Kim, Han-Suk Kim

“…The DAP value per X-ray decreased by 42.6%, from an average of 0.25 to 0.14 (p=0.011). …”
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An anthropomorphic phantom for atrial transseptal puncture simulation training by Aya Mutaz Zeidan, Zhouyang Xu, Lisa Leung, Calum Byrne, Sachin Sabu, Yijia Zhou, Christopher Aldo Rinaldi, John Whitaker, Steven E. Williams, Jonathan Behar, Aruna Arujuna, R. James Housden, Kawal Rhode

“…This study presents a novel, patient-specific, anthropomorphic phantom for TSP simulation training that can be used with X-ray fluoroscopy and ultrasound imaging. …”
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Automatic Fracture Detection Convolutional Neural Network with Multiple Attention Blocks Using Multi-Region X-Ray Data by Rashadul Islam Sumon, Mejbah Ahammad, Md Ariful Islam Mozumder, Md Hasibuzzaman, Salam Akter, Hee-Cheol Kim, Mohammad Hassan Ali Al-Onaizan, Mohammed Saleh Ali Muthanna, Dina S. M. Hassan

“…The training and evaluation dataset consists of fractured and non-fractured X-rays from various anatomical locations, including the hips, knees, lumbar region, lower limb, and upper limb. …”
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Enhanced Multi-Model Deep Learning for Rapid and Precise Diagnosis of Pulmonary Diseases Using Chest X-Ray Imaging by Rahul Kumar, Cheng-Tang Pan, Yi-Min Lin, Shiue Yow-Ling, Ting-Sheng Chung, Uyanahewa Gamage Shashini Janesha

“…EMDL integrates an ensemble of five pre-trained deep learning models (VGG-16, VGG-19, ResNet, AlexNet, and GoogleNet) with advanced image preprocessing (histogram equalization and contrast enhancement) and a novel multi-stage feature selection and optimization pipeline (PCA, SelectKBest, Binary Particle Swarm Optimization (BPSO), and Binary Grey Wolf Optimization (BGWO)). …”
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Towards Automatic Detection of Pneumothorax in Emergency Care with Deep Learning Using Multi-Source Chest X-ray Data by Santiago Ibañez Caturla, Juan de Dios Berná Mestre, Oscar Martinez Mozos

“…A convolutional neural network (CNN) with an EfficientNet architecture is trained and optimized to identify radiographic signs of pneumothorax using those public datasets. …”
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