This study compares dual-energy computed tomography (DECT) images of a phantom including different material inserts and with additional lateral titanium or stainless steel inserts, simulating bilateral hip prostheses. Dual-source (DS) and fast kV-switching (FKS) DECT with/without metal artefact reduction (MAR) were compared with regards to virtually monoenergetic CT number accuracy and the depiction of different materials. Streak artefacts were observed between the metal inserts that were more severe with steel compared to titanium inserts. The artefact severity and CT number accuracy depended on the photon energy (keV) for both DECT techniques. While MAR generally increased the CT number accuracy and material depiction within the streak artefacts, it sometimes decreased the accuracy outside the streak artefacts for both DS and FKS. FKS depicted the metal inserts more accurately than DS with regards to both CT numbers and external diameter.
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http://dx.doi.org/10.1093/rpd/ncab105 | DOI Listing |
Ir J Med Sci
January 2025
Faculty of Medicine, Department of Pediatric Surgery Division of Pediatric Urology, Eskisehir Osmangazi University, Eskişehir, Turkey.
Background: Hydronephrosis developing at the ureteropelvic junction due to obstruction poses clinical challenges as it has the potential to cause renal damage.
Aims: This study aims to evaluate how well machine learning models such, as XGBClassifier and Logistic Regression can be used to predict the need for treatment in patients, with hydronephrosis resulting from ureteropelvic junction obstruction.
Methods: Hydronephrosis was diagnosed in the medical records of patients from January 2015 to December 2020.
Int Endod J
January 2025
Department of Oral and Maxillofacial Surgery, Guangdong Engineering Research Center of Oral Restoration and Reconstruction Guangzhou Key Laboratory of Basic and Applied Research of Oral Regenerative Medicine, Affiliated Stomatology Hospital of Guangzhou Medical University, Guangzhou, China.
Aim: Autotransplantation of teeth (ATT) is a viable biological method for addressing dental defects. The objective was to achieve occlusal reconstruction-orientated ATT to enhance functionality and obtain optimal location and adjacency. This study proposes a new concept of a guide (a fully guided system) to achieve position-predictable ATT.
View Article and Find Full Text PDFAnal Chem
January 2025
State Key Laboratory of Cellular Stress Biology, Institute of Artificial Intelligence, School of Life Sciences, Faculty of Medicine and Life Sciences, National Institute for Data Science in Health and Medicine, XMU-HBN skin biomedical research center, Xiamen University, Xiamen, Fujian 361102, China.
In metabolomic analysis based on liquid chromatography coupled with mass spectrometry, detecting and quantifying intricate objects is a massive job. Current peak picking methods still cause high rates of incorrectly picked peaks to influence the reliability and reproducibility of results. To address these challenges, we developed QuanFormer, a deep learning method based on object detection designed to accurately quantify peak signals.
View Article and Find Full Text PDFRapid technological advancements have made it possible to generate single-cell data at a large scale. Several laboratories around the world can now generate single-cell transcriptomic data from different tissues. Unsupervised clustering, followed by annotation of the cell type of the identified clusters, is a crucial step in single-cell analyses.
View Article and Find Full Text PDFiScience
January 2025
Cognitive Neuroimaging Unit, CEA, INSERM, Université Paris-Saclay, NeuroSpin Center, 91191 Gif/Yvette, France.
Recent studies showed that humans, regardless of age, education, and culture, can extract the linear trend of a noisy scatterplot. Although this capacity looks sophisticated, it may simply reflect the extraction of the principal trend of the graph, as if the cloud of dots was processed as an oriented object. To test this idea, we trained Guinea baboons to associate arbitrary shapes with the increasing or decreasing trends of noiseless and noisy scatterplots, while varying the number of points, the noise level, and the regression slope.
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