AIMC Topic: Radiographic Image Interpretation, Computer-Assisted

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Artificial intelligence-derived coronary artery calcium scoring saves time and achieves close to radiologist-level accuracy accuracy on routine ECG-gated CT.

The international journal of cardiovascular imaging Dec 16, 2024
Artificial Intelligence (AI) has been proposed to improve workflow for coronary artery calcium scoring (CACS), but simultaneous demonstration of improved efficiency, accuracy, and clinical stability have not been demonstrated. 148 sequential patients...
Reproducibility of Results Coronary Artery Disease Aged Workflow Male Observer Variation Middle Aged Predictive Value of Tests Coronary Vessels Humans Coronary Angiography Artificial Intelligence Multidetector Computed Tomography Radiologists Retrospective Studies Vascular Calcification Severity of Illness Index Radiographic Image Interpretation, Computer-Assisted Female Computed Tomography Angiography Time Factors Cardiac-Gated Imaging Techniques Electrocardiography
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Feasibility of Sub-milliSievert Low-dose Computed Tomography with Deep Learning Image Reconstruction in Evaluating Pulmonary Subsolid Nodules: A Prospective Intra-individual Comparison Study.

Academic radiology Dec 13, 2024
RATIONALE AND OBJECTIVES: To comprehensively assess the feasibility of low-dose computed tomography (LDCT) using deep learning image reconstruction (DLIR) for evaluating pulmonary subsolid nodules, which are challenging due to their susceptibility to...
Middle Aged Deep Learning Lung Neoplasms Female Humans Radiographic Image Interpretation, Computer-Assisted Multiple Pulmonary Nodules Aged Prospective Studies Feasibility Studies Adult Tomography, X-Ray Computed Radiation Dosage Male Signal-To-Noise Ratio
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Spectrum of errors in nodule detection and characterization using machine learning: A pictorial essay.

Current problems in diagnostic radiology Dec 10, 2024
In academic and research settings, computer-aided nodule detection software has been shown to increase accuracy, efficiency, and throughput. However, radiologists need to be familiar with the spectrum of errors that can occur when these algorithms ar...
Diagnostic Errors Machine Learning Lung Neoplasms Humans Algorithms Solitary Pulmonary Nodule Tomography, X-Ray Computed Radiographic Image Interpretation, Computer-Assisted
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Breast cancer detection and classification with digital breast tomosynthesis: a two-stage deep learning approach.

Diagnostic and interventional radiology (Ankara, Turkey) Dec 9, 2024
PURPOSE: The purpose of this study was to propose a new computer-assisted two-staged diagnosis system that combines a modified deep learning (DL) architecture (VGG19) for the classification of digital breast tomosynthesis (DBT) images with the detect...
Mammography Radiographic Image Interpretation, Computer-Assisted Breast Humans Female Aged Adult Breast Neoplasms Middle Aged Deep Learning
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Domain generalization for mammographic image analysis with contrastive learning.

Computers in biology and medicine Dec 9, 2024
The deep learning technique has been shown to be effectively addressed several image analysis tasks in the computer-aided diagnosis scheme for mammography. The training of an efficacious deep learning model requires large data with diverse styles and...
Breast Deep Learning Image Processing, Computer-Assisted Mammography Radiographic Image Interpretation, Computer-Assisted Humans Female Breast Neoplasms
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Comparative study of DCNN and image processing based classification of chest X-rays for identification of COVID-19 patients using fine-tuning.

Journal of medical engineering & technology Dec 9, 2024
The conventional detection of COVID-19 by evaluating the CT scan images is tiresome, often experiences high inter-observer variability and uncertainty issues. This work proposes the automatic detection and classification of COVID-19 by analysing the ...
Deep Learning COVID-19 Image Processing, Computer-Assisted Humans Algorithms Radiography, Thoracic Radiographic Image Interpretation, Computer-Assisted Neural Networks, Computer Tomography, X-Ray Computed Betacoronavirus Coronavirus Infections Pandemics SARS-CoV-2 Pneumonia, Viral
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Comparing fully automated AI body composition biomarkers at differing virtual monoenergetic levels using dual-energy CT.

Abdominal radiology (New York) Dec 7, 2024
PURPOSE: To investigate the behavior of artificial intelligence (AI) CT-based body composition biomarkers at different virtual monoenergetic imaging (VMI) levels using dual-energy CT (DECT).
Humans Artificial Intelligence Algorithms Biomarkers Aged, 80 and over Adult Male Middle Aged Retrospective Studies Tomography, X-Ray Computed Female Aged Radiography, Dual-Energy Scanned Projection Contrast Media Body Composition Radiographic Image Interpretation, Computer-Assisted
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Deep Learning for Contrast Enhanced Mammography - A Systematic Review.

Academic radiology Dec 5, 2024
BACKGROUND/AIM: Contrast-enhanced mammography (CEM) is a relatively novel imaging technique that enables both anatomical and functional breast imaging, with improved diagnostic performance compared to standard 2D mammography. The aim of this study is...
Deep Learning Contrast Media Mammography Radiographic Image Interpretation, Computer-Assisted Radiographic Image Enhancement Humans Female Breast Neoplasms
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MLVICX: Multi-Level Variance-Covariance Exploration for Chest X-Ray Self-Supervised Representation Learning.

IEEE journal of biomedical and health informatics Dec 5, 2024
Self-supervised learning (SSL) reduces the need for manual annotation in deep learning models for medical image analysis. By learning the representations from unablelled data, self-supervised models perform well on tasks that require little to no fin...
Deep Learning Radiographic Image Interpretation, Computer-Assisted Supervised Machine Learning Radiography, Thoracic Humans Lung
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Leveraging deep transfer learning and explainable AI for accurate COVID-19 diagnosis: Insights from a multi-national chest CT scan study.

Computers in biology and medicine Dec 3, 2024
The COVID-19 pandemic has emerged as a global health crisis, impacting millions worldwide. Although chest computed tomography (CT) scan images are pivotal in diagnosing COVID-19, their manual interpretation by radiologists is time-consuming and poten...
SARS-CoV-2 Deep Learning Radiographic Image Interpretation, Computer-Assisted Coronavirus Infections COVID-19 Tomography, X-Ray Computed Reproducibility of Results Humans Neural Networks, Computer Pandemics Betacoronavirus Pneumonia, Viral
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