AIMC Topic: Tomography, X-Ray Computed

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Classifying age from medial clavicle using a 30-year threshold: An image analysis based approach.

PloS one Nov 22, 2024
This study aimed to develop image-analysis-based classification models for distinguishing individuals younger and older than 30 using the medial clavicle. We extracted 2D images of the medial clavicle from multi-slice computed tomography (MSCT) scans...
Male Middle Aged Humans Image Processing, Computer-Assisted Support Vector Machine Clavicle Neural Networks, Computer Age Factors Logistic Models Female Tomography, X-Ray Computed Principal Component Analysis Aged Age Determination by Skeleton Young Adult Adult
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Artificial intelligence in respiratory pandemics-ready for disease X? A scoping review.

European radiology Nov 21, 2024
OBJECTIVES: This study aims to identify repeated previous shortcomings in medical imaging data collection, curation, and AI-based analysis during the early phase of respiratory pandemics. Based on the results, it seeks to highlight essential steps fo...
Humans Artificial Intelligence Pandemics COVID-19 Tomography, X-Ray Computed SARS-CoV-2 Influenza, Human Influenza A Virus, H1N1 Subtype Severe Acute Respiratory Syndrome
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A Physics-Informed Deep Neural Network for Harmonization of CT Images.

IEEE transactions on bio-medical engineering Nov 21, 2024
OBJECTIVE: Computed Tomography (CT) quantification is affected by the variability in image acquisition and rendition. This paper aimed to reduce this variability by harmonizing the images utilizing physics-based deep neural networks (DNNs).
Humans Neural Networks, Computer Image Processing, Computer-Assisted Radiographic Image Interpretation, Computer-Assisted Lung Diseases Phantoms, Imaging Algorithms Tomography, X-Ray Computed Lung Deep Learning
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Artificial intelligence contouring in radiotherapy for organs-at-risk and lymph node areas.

Radiation oncology (London, England) Nov 21, 2024
INTRODUCTION: The delineation of organs-at-risk and lymph node areas is a crucial step in radiotherapy, but it is time-consuming and associated with substantial user-dependent variability in contouring. Artificial intelligence (AI) appears to be the ...
Organs at Risk Radiotherapy Planning, Computer-Assisted Male Child Lymph Nodes Magnetic Resonance Imaging Humans Tomography, X-Ray Computed Artificial Intelligence Female Software Adult
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Resolution-dependent MRI-to-CT translation for orthotopic breast cancer models using deep learning.

Physics in medicine and biology Nov 21, 2024
This study aims to investigate the feasibility of utilizing generative adversarial networks (GANs) to synthesize high-fidelity computed tomography (CT) images from lower-resolution MR images. The goal is to reduce patient exposure to ionizing radiati...
Mice, Nude Mice, Inbred BALB C Cell Line, Tumor Image Processing, Computer-Assisted Humans Mice Female Tomography, X-Ray Computed Magnetic Resonance Imaging Breast Neoplasms Animals Deep Learning
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An AI deep learning algorithm for detecting pulmonary nodules on ultra-low-dose CT in an emergency setting: a reader study.

European radiology experimental Nov 20, 2024
BACKGROUND: To retrospectively assess the added value of an artificial intelligence (AI) algorithm for detecting pulmonary nodules on ultra-low-dose computed tomography (ULDCT) performed at the emergency department (ED).
Solitary Pulmonary Nodule Tomography, X-Ray Computed Emergency Service, Hospital Female Radiation Dosage Aged Male Artificial Intelligence Middle Aged Algorithms Deep Learning Prospective Studies Lung Neoplasms Retrospective Studies Multiple Pulmonary Nodules Humans
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A systematic review on feature extraction methods and deep learning models for detection of cancerous lung nodules at an early stage -the recent trends and challenges.

Biomedical physics & engineering express Nov 20, 2024
Lung cancer is one of the most common life-threatening worldwide cancers affecting both the male and the female populations. The appearance of nodules in the scan image is an early indication of the development of cancer cells in the lung. The Low Do...
Early Detection of Cancer Radiographic Image Interpretation, Computer-Assisted Lung Deep Learning Humans Image Processing, Computer-Assisted Lung Neoplasms Neural Networks, Computer Algorithms Tomography, X-Ray Computed
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Prediction of benign and malignant pulmonary nodules using preoperative CT features: using PNI-GARS as a predictor.

Frontiers in immunology Nov 20, 2024
PURPOSE: The aim of this study was to develop and validate a prediction model for classification of pulmonary nodules based on preoperative CT imaging.
Solitary Pulmonary Nodule Humans Tomography, X-Ray Computed Male Machine Learning Female Middle Aged Retrospective Studies Aged Lung Neoplasms Adult Multiple Pulmonary Nodules
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Using machine learning to develop a stacking ensemble learning model for the CT radiomics classification of brain metastases.

Scientific reports Nov 19, 2024
The objective of this study was to explore the potential of machine-learning techniques in the automatic identification and classification of brain metastases from a radiomic perspective, aiming to improve the accuracy of tumor volume assessment for ...
Support Vector Machine Tumor Burden Brain Tomography, X-Ray Computed Female Aged Radiomics Brain Neoplasms Male Middle Aged Humans Neural Networks, Computer Machine Learning Algorithms
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Computer tomography-based radiomics combined with machine learning for predicting the time since onset of epidural hematoma.

International journal of legal medicine Nov 18, 2024
Estimation of the age of epidural hematoma (EDH) is a challenge in clinical forensic medicine, and this issue has yet to be conclusively resolved. The advantages of objectivity and non-invasiveness make computing tomography (CT) imaging an potential ...
Algorithms Tomography, X-Ray Computed Female Aged Humans Machine Learning Middle Aged Adolescent Time Factors Hematoma, Epidural, Cranial Young Adult Adult Radiomics Male
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