AIMC Topic: Deep Learning

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Assessment of Image Quality of Coronary Computed Tomography Angiography in Obese Patients by Comparing Deep Learning Image Reconstruction With Adaptive Statistical Iterative Reconstruction Veo.

Journal of computer assisted tomography May 13, 2025
OBJECTIVE: The aim of the study was to evaluate the image quality of coronary computed tomography (CT) angiography (CCTA) in obese patients by using deep learning image reconstruction (DLIR) in comparison with adaptive statistical iterative reconstru...
Male Middle Aged Deep Learning Female Aged Adult Coronary Vessels Radiation Dosage Computed Tomography Angiography Obesity Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Humans Prospective Studies
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In Vitro Study of the Precision and Accuracy of Measurement of the Vascular Inner Diameter on Computed Tomography Angiography Using Deep Learning Image Reconstruction: Comparison With Filtered Back Projection and Iterative Reconstruction.

Journal of computer assisted tomography May 13, 2025
OBJECTIVE: This study aimed to compare the performance of deep learning image reconstruction (DLIR) with that of standard filtered back projection (FBP) and adaptive statistical iterative reconstruction V (ASiR-V) for measurement of the vascular diam...
Models, Cardiovascular Radiographic Image Interpretation, Computer-Assisted Phantoms, Imaging Computed Tomography Angiography Algorithms Deep Learning
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Deep Learning-Based CT Radiomics for Feature Representation and Analysis of Aging Characteristics of Asian Bony Orbit.

The Journal of craniofacial surgery May 13, 2025
OBJECTIVE: This paper puts forward a new method for automatic segmentation of bony orbit as well as automatic extraction and classification of aging features of segmented orbit contour based on depth learning, with which the aging mode of bony orbit ...
Deep Learning Humans Orbit Tomography, X-Ray Computed Asian People Female Aged Male Adult Aging Middle Aged
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Evaluating a Convolutional Neural Network Noise Reduction Method When Applied to CT Images Reconstructed Differently Than Training Data.

Journal of computer assisted tomography May 13, 2025
OBJECTIVE: The aim of this study was to evaluate a narrowly trained convolutional neural network (CNN) denoising algorithm when applied to images reconstructed differently than training data set.
Signal-To-Noise Ratio Humans Tomography, X-Ray Computed Neural Networks, Computer Deep Learning Algorithms Image Processing, Computer-Assisted
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Deep Learning for Retinal Image Quality Assessment of Optic Nerve Head Disorders.

Asia-Pacific journal of ophthalmology (Philadelphia, Pa.) May 13, 2025
Deep learning (DL)-based retinal image quality assessment (RIQA) algorithms have been gaining popularity, as a solution to reduce the frequency of diagnostically unusable images. Most existing RIQA tools target retinal conditions, with a dearth of st...
Optic Nerve Diseases Deep Learning Fundus Oculi Humans Optic Disk
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Interpreting Deep Learning Studies in Glaucoma: Unresolved Challenges.

Asia-Pacific journal of ophthalmology (Philadelphia, Pa.) May 13, 2025
Deep learning algorithms as tools for automated image classification have recently experienced rapid growth in imaging-dependent medical specialties, including ophthalmology. However, only a few algorithms tailored to specific health conditions have ...
Visual Field Tests Diagnostic Techniques, Ophthalmological Glaucoma Deep Learning Tomography, Optical Coherence Humans
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Deep Learning-Based Optical Coherence Tomography and Optical Coherence Tomography Angiography Image Analysis: An Updated Summary.

Asia-Pacific journal of ophthalmology (Philadelphia, Pa.) May 13, 2025
Deep learning (DL) is a subset of artificial intelligence based on deep neural networks. It has made remarkable breakthroughs in medical imaging, particularly for image classification and pattern recognition. In ophthalmology, there are rising intere...
Humans Deep Learning Tomography, Optical Coherence Angiography
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Initial Experience With Low-Dose 18F-Fluorodeoxyglucose Positron Emission Tomography/Magnetic Resonance Imaging With Deep Learning Enhancement.

Journal of computer assisted tomography May 13, 2025
OBJECTIVE: To demonstrate the utility of deep learning enhancement (DLE) to achieve diagnostic quality low-dose positron emission tomography (PET)/magnetic resonance (MR) imaging.
Radiopharmaceuticals Positron-Emission Tomography Image Interpretation, Computer-Assisted Fluorodeoxyglucose F18 Deep Learning Magnetic Resonance Imaging Multimodal Imaging Male Middle Aged Humans Female Aged Young Adult Adult
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Use of a Dual Artificial Intelligence Platform to Detect Unreported Lung Nodules.

Journal of computer assisted tomography May 13, 2025
OBJECTIVE: To investigate the performance of Dual-AI Deep Learning Platform in detecting unreported pulmonary nodules that are 6 mm or greater, comprising computer-vision (CV) algorithm to detect pulmonary nodules, with positive results filtered by n...
Deep Learning Adolescent Multiple Pulmonary Nodules Middle Aged Algorithms Female Humans Lung Young Adult Retrospective Studies Aged Artificial Intelligence Natural Language Processing Adult Tomography, X-Ray Computed Aged, 80 and over Radiographic Image Interpretation, Computer-Assisted Male
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YOLO-TARC: YOLOv10 with Token Attention and Residual Convolution for Small Void Detection in Root Canal X-Ray Images.

Sensors (Basel, Switzerland) May 12, 2025
The detection of small voids or defects in X-ray images of tooth root canals still faces challenges. To address the issue, this paper proposes an improved YOLOv10 that combines Token Attention with Residual Convolution (ResConv), termed YOLO-TARC. To...
Dental Pulp Cavity Image Processing, Computer-Assisted X-Rays Humans Algorithms Deep Learning
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