Biomedical physics & engineering express
Aug 19, 2022
Low Performing Pixel (LPP)/bad pixel in CT detectors cause ring and streaks artifacts, structured non-uniformities and deterioration of the image quality. These artifacts make the image unusable for diagnostic purposes. A missing/defective detector p...
Computational and mathematical methods in medicine
Aug 19, 2022
Traditional image segmentation methods often encounter problems of low segmentation accuracy and being time-consuming when processing complex tooth Computed Tomography (CT) images. This paper proposes an improved segmentation method for tooth CT imag...
BACKGROUND: Whole-body low-dose CT is the recommended initial imaging modality to evaluate bone destruction as a result of multiple myeloma. Accurate interpretation of these scans to detect small lytic bone lesions is time intensive. A functional dee...
This research aimed to investigate the diagnostic effect of computed tomography (CT) images based on a deep learning double residual convolution neural network (DRCNN) model on chronic obstructive pulmonary disease (COPD) and the related risk factors...
Acta radiologica (Stockholm, Sweden : 1987)
Aug 17, 2022
BACKGROUND: The demand for homogeneous and higher vascular contrast enhancement is critical to provide an appropriate interpretation of abnormal vascular findings in coronary computed tomography angiography (CTA).
Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
Aug 17, 2022
Interstitial lung disease (ILD), representing a collection of disorders, is considered to be the deadliest one, which increases the mortality rate of humans. In this paper, an automated scheme for detection and classification of ILD patterns is prese...
PURPOSE: We employ nnU-Net, a state-of-the-art self-configuring deep learning-based semantic segmentation method for quantitative visualization of hemothorax (HTX) in trauma patients, and assess performance using a combination of overlap and volume-b...
European journal of cancer (Oxford, England : 1990)
Aug 16, 2022
BACKGROUND: The need for developing new biomarkers is increasing with the emergence of many targeted therapies. Artificial Intelligence (AI) algorithms have shown great promise in the medical imaging field to build predictive models. We developed a p...
PURPOSE: To develop a novel multimodal data fusion model by incorporating computed tomography (CT) images and clinical variables based on deep learning for predicting the invasiveness risk of stage I lung adenocarcinoma that manifests as ground-glass...
Medical & biological engineering & computing
Aug 13, 2022
High-quality computed tomography (CT) images are key to clinical diagnosis. However, the current quality of an image is limited by reconstruction algorithms and other factors and still needs to be improved. When using CT, a large quantity of imaging ...
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