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Development of a CT radiomics prognostic model for post renal tumor resection overall survival based on transformer enhanced K-means clustering.
Med Phys
January 2025
Department of Oncology, The Affiliated Hospital of Southwest Medical University, Luzhou, China.
Background: Kidney tumors, common in the urinary system, have widely varying survival rates post-surgery. Current prognostic methods rely on invasive biopsies, highlighting the need for non-invasive, accurate prediction models to assist in clinical decision-making.
Purpose: This study aimed to construct a K-means clustering algorithm enhanced by Transformer-based feature transformation to predict the overall survival rate of patients after kidney tumor resection and provide an interpretability analysis of the model to assist in clinical decision-making.
Optimization of x-ray dark-field CT for human-scale lung imaging.
Med Phys
January 2025
Department of Engineering Physics, Tsinghua University, Beijing, China.
Background: X-ray grating-based dark-field imaging can sense the small angle scattering caused by object's micro-structures. This technique is sensitive to the porous microstructure of lung alveoli and has the potential to detect lung diseases at an early stage. Up to now, a human-scale dark-field CT (DF-CT) prototype has been built for lung imaging.
View Article and Find Full Text PDFAge determination by measurement of pulp volume of canine teeth in patients with cleft lip and palate: a retrospective study.
Oral Radiol
January 2025
Faculty of Dentistry, Department of Oral and Maxillofacial Radiology, Istanbul University, Istanbul, Turkey.
Objectives: This study evaluates the potential of pulp volume/total tooth-volume measurements of canine teeth in relation to chronologic age in patients with cleft lip and palate (CLP). The significance of this study lies in its exploration of the usability of these measurements for age determination in CLP patients, providing a novel perspective to the existing literature.
Methods: Cone beam computed tomography images of 33 patients (16 females, 17 males) with unilateral CLP aged 14-45 years and 33 age- and sex-matched healthy individuals (16 females, 17 males) were retrospectively evaluated.
Systematic Review of Hybrid Vision Transformer Architectures for Radiological Image Analysis.
J Imaging Inform Med
January 2025
School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA.
Vision transformer (ViT)and convolutional neural networks (CNNs) each possess distinct strengths in medical imaging: ViT excels in capturing long-range dependencies through self-attention, while CNNs are adept at extracting local features via spatial convolution filters. While ViT may struggle with capturing detailed local spatial information, critical for tasks like anomaly detection in medical imaging, shallow CNNs often fail to effectively abstract global context. This study aims to explore and evaluate hybrid architectures that integrate ViT and CNN to leverage their complementary strengths for enhanced performance in medical vision tasks, such as segmentation, classification, reconstruction, and prediction.
View Article and Find Full Text PDFBrain Midline Approximation to Improve Symmetry Analysis of Brain CT Scans.
J Imaging Inform Med
January 2025
Faculty of Mathematics and Information Science, Warsaw University of Technology, Warsaw, Poland.
Analysis of the symmetry of the brain hemispheres at the level of individual structures and dominant tissue features has been the subject of research for many years in the context of improving the effectiveness of imaging methods for the diagnosis of brain tumor, stroke, and Alzheimer's disease, among others. One useful approach is to reliably determine the midline of the brain, which allows comparative analysis of the hemispheres and uncovers information on symmetry/asymmetry in the relevant planes of, for example, CT scans. Therefore, an effective method that is robust to various geometric deformations, artifacts, varying noise characteristics, and natural anatomical variability is sought.
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