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3D CT to 2D X-ray image registration for improved visualization of tibial vessels in endovascular procedures.
Int J Comput Assist Radiol Surg
January 2025
Department of Medical Biophysics, University of Toronto, Toronto, Canada.
Purpose: During endovascular revascularization interventions for peripheral arterial disease, the standard modality of X-ray fluoroscopy (XRF) used for image guidance is limited in visualizing distal segments of infrapopliteal vessels. To enhance visualization of arteries, an image registration technique was developed to align pre-acquired computed tomography (CT) angiography images and to create fusion images highlighting arteries of interest.
Methods: X-ray image metadata capturing the position of the X-ray gantry initializes a multiscale iterative optimization process, which uses a local-variance masked normalized cross-correlation loss to rigidly align a digitally reconstructed radiograph (DRR) of the CT dataset with the target X-ray, using the edges of the fibula and tibia as the basis for alignment.
Enhancing security and efficiency in Mobile Ad Hoc Networks using a hybrid deep learning model for flooding attack detection.
Sci Rep
January 2025
North Carolina School of Science and Mathematics, Durham, NC, 27705, USA.
Mobile Ad Hoc Networks (MANETs) are increasingly replacing conventional communication systems due to their decentralized and dynamic nature. However, their wireless architecture makes them highly vulnerable to flooding attacks, which can disrupt communication, deplete energy resources, and degrade network performance. This study presents a novel hybrid deep learning approach integrating Convolutional Neural Networks (CNN) with Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) architectures to effectively detect and mitigate flooding attacks in MANETs.
View Article and Find Full Text PDFDevelopment and validation of a new nomogram for self-reported OA based on machine learning: a cross-sectional study.
Sci Rep
January 2025
Department of Rheumatology and Immunology, The First Affiliated Hospital of Shantou University Medical College, Shantou, 515041, China.
Developing a new diagnostic prediction model for osteoarthritis (OA) to assess the likelihood of individuals developing OA is crucial for the timely identification of potential populations of OA. This allows for further diagnosis and intervention, which is significant for improving patient prognosis. Based on the NHANES for the periods of 2011-2012, 2013-2014, and 2015-2016, the study involved 11,366 participants, of whom 1,434 reported a diagnosis of OA.
View Article and Find Full Text PDFPrediction of pulmonary embolism by an explainable machine learning approach in the real world.
Sci Rep
January 2025
Department of Respiratory and Critical Care Medicine, Changhai Hospital, The Second Military Medical University, Shanghai, People's Republic of China.
In recent years, large amounts of researches showed that pulmonary embolism (PE) has become a common disease, and PE remains a clinical challenge because of its high mortality, high disability, high missed and high misdiagnosed rates. To address this, we employed an artificial intelligence-based machine learning algorithm (MLA) to construct a robust predictive model for PE. We retrospectively analyzed 1480 suspected PE patients hospitalized in West China Hospital of Sichuan University between May 2015 and April 2020.
View Article and Find Full Text PDFUsing the Nutri-Score to visualise food reformulation in Germany: the case of breakfast cereals.
BMC Public Health
January 2025
Department of Nutritional Behaviour, Max Rubner-Institut (MRI) - Federal Research Institute of Nutrition and Food, Haid-und-Neu-Straße 9, 76131, Karlsruhe, Germany.
Background: The reformulation of commonly consumed foods towards less sugar, fat, and salt is an important public health strategy to improve food choices of consumers and thus address the high prevalence of overweight and obesity. Front-of-pack nutrition labels like the Nutri-Score may drive reformulation and support nutritionally favourable food choices. Breakfast cereals are of special interest in that they tend to be high in sugar and are relatively often targeted at children.
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