AIMC Topic: Paranasal Sinuses

Clear Filters Showing 11 to 14 of 14 articles

An artificial intelligence algorithm that identifies middle turbinate pneumatisation (concha bullosa) on sinus computed tomography scans.

The Journal of laryngology and otology Apr 1, 2020
OBJECTIVE: Convolutional neural networks are a subclass of deep learning or artificial intelligence that are predominantly used for image analysis and classification. This proof-of-concept study attempts to train a convolutional neural network algori...
Turbinates Artificial Intelligence Neural Networks, Computer Retrospective Studies Algorithms Humans Paranasal Sinuses Australia Nose Diseases Tomography, X-Ray Computed Male Observer Variation Female
View on PubMed DOI

Automated classification of osteomeatal complex inflammation on computed tomography using convolutional neural networks.

International forum of allergy & rhinology Aug 11, 2018
BACKGROUND: Convolutional neural networks (CNNs) are advanced artificial intelligence algorithms well suited to image classification tasks with variable features. These have been used to great effect in various real-world applications including handw...
Automation, Laboratory Rhinitis Nasal Obstruction Tomography, X-Ray Computed Adult Chronic Disease Paranasal Sinuses Prospective Studies Sinusitis Female Neural Networks, Computer Humans Artificial Intelligence Inflammation Male
View on PubMed DOI

Machine learning framework for simulation of artifacts in paranasal sinuses diagnosis using CT images.

Journal of X-ray science and technology Jan 1, 2024
In the medical field, diagnostic tools that make use of deep neural networks have reached a level of performance never before seen. A proper diagnosis of a patient's condition is crucial in modern medicine since it determines whether or not the patie...
Algorithms Tomography, X-Ray Computed Machine Learning Artifacts Paranasal Sinus Diseases Paranasal Sinuses Image Processing, Computer-Assisted Humans
View on PubMed DOI

Prediction of age and sex from paranasal sinus images using a deep learning network.

Medicine Feb 19, 2021
This study was conducted to develop a convolutional neural network (CNN)-based model to predict the sex and age of patients by identifying unique unknown features from paranasal sinus (PNS) X-ray images.We employed a retrospective study design and us...
Aged Adult Female Middle Aged Deep Learning Male Sensitivity and Specificity Algorithms Retrospective Studies Databases, Factual Humans Neural Networks, Computer Paranasal Sinuses Predictive Value of Tests Data Management Radiography Area Under Curve Maxillary Sinus
View on PubMed DOI
Popular Topics
Recent Journals