AIMC Topic: Tomography, Spiral Computed
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Automated detection and classification of mandibular fractures on multislice spiral computed tomography using modified convolutional neural networks.
Oral surgery, oral medicine, oral pathology and oral radiology
Aug 5, 2024
OBJECTIVE: To evaluate the performance of convolutional neural networks (CNNs) for the automated detection and classification of mandibular fractures on multislice spiral computed tomography (MSCT).
Machine Learning Model Based on Radiomics for Preoperative Differentiation of Jaw Cystic Lesions.
Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery
Apr 1, 2024
OBJECTIVE: This study aims to use machine learning techniques together with radiomics methods to build a preoperative predictive diagnostic model from spiral computed tomography (CT) images. The model is intended for the differential diagnosis of com...
Reducing windmill artifacts in clinical spiral CT using a deep learning-based projection raw data upsampling: Method and robustness evaluation.
Medical physics
Jan 16, 2024
BACKGROUND: Multislice spiral computed tomography (MSCT) requires an interpolation between adjacent detector rows during backprojection. Not satisfying the Nyquist sampling condition along the z-axis results in aliasing effects, also known as windmil...
Diagnosis of Liver Cirrhosis and Liver Fibrosis by Artificial Intelligence Algorithm-Based Multislice Spiral Computed Tomography.
Computational and mathematical methods in medicine
Mar 15, 2022
This research was aimed at investigating the artificial intelligence (AI) segmentation algorithm-based multislice spiral computed tomography (MSCT) in the diagnosis of liver cirrhosis and liver fibrosis. Besides, it was aimed at providing new methods...
A dual-domain deep learning-based reconstruction method for fully 3D sparse data helical CT.
Physics in medicine and biology
Dec 11, 2020
Helical CT has been widely used in clinical diagnosis. In this work, we focus on a new prototype of helical CT, equipped with sparsely spaced multidetector and multi-slit collimator (MSC) in the axis direction. This type of system can not only lower ...
Preoperative Prediction of Pancreatic Neuroendocrine Neoplasms Grading Based on Enhanced Computed Tomography Imaging: Validation of Deep Learning with a Convolutional Neural Network.
Neuroendocrinology
Sep 13, 2019
INTRODUCTION: The pathological grading of pancreatic neuroendocrine neoplasms (pNENs) is an independent predictor of survival and indicator for treatment. Deep learning (DL) with a convolutional neural network (CNN) may improve the preoperative predi...
Dynamic contrast-enhanced computed tomography diagnosis of primary liver cancers using transfer learning of pretrained convolutional neural networks: Is registration of multiphasic images necessary?
International journal of computer assisted radiology and surgery
May 3, 2019
PURPOSE: To evaluate the effect of image registration on the diagnostic performance of transfer learning (TL) using pretrained convolutional neural networks (CNNs) and three-phasic dynamic contrast-enhanced computed tomography (DCE-CT) for primary li...
Zero-Echo-Time and Dixon Deep Pseudo-CT (ZeDD CT): Direct Generation of Pseudo-CT Images for Pelvic PET/MRI Attenuation Correction Using Deep Convolutional Neural Networks with Multiparametric MRI.
Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Oct 30, 2017
Accurate quantification of uptake on PET images depends on accurate attenuation correction in reconstruction. Current MR-based attenuation correction methods for body PET use a fat and water map derived from a 2-echo Dixon MRI sequence in which bone ...
Fuzzy Clustering Applied to ROI Detection in Helical Thoracic CT Scans with a New Proposal and Variants.
BioMed research international
Jul 18, 2016
The detection of pulmonary nodules is one of the most studied problems in the field of medical image analysis due to the great difficulty in the early detection of such nodules and their social impact. The traditional approach involves the developmen...
Research on the effectiveness of multi-view slice correction strategy based on deep learning in high pitch helical CT reconstruction.
Journal of X-ray science and technology
Jan 1, 2024
BACKGROUND: Recent studies have explored layered correction strategies, employing a slice-by-slice approach to mitigate the prominent limited-view artifacts present in reconstructed images from high-pitch helical CT scans. However, challenges persist...
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