AIMC Topic: Radiography, Thoracic
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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 ...
Intersection of Performance, Interpretability, and Fairness in Neural Prototype Tree for Chest X-Ray Pathology Detection: Algorithm Development and Validation Study.
JMIR formative research
Dec 5, 2024
BACKGROUND: While deep learning classifiers have shown remarkable results in detecting chest X-ray (CXR) pathologies, their adoption in clinical settings is often hampered by the lack of transparency. To bridge this gap, this study introduces the neu...
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...
Multi-Label Chest X-Ray Image Classification With Single Positive Labels.
IEEE transactions on medical imaging
Dec 2, 2024
Deep learning approaches for multi-label Chest X-ray (CXR) images classification usually require large-scale datasets. However, acquiring such datasets with full annotations is costly, time-consuming, and prone to noisy labels. Therefore, we introduc...
Lightweight convolutional neural network for chest X-ray images classification.
Scientific reports
Nov 30, 2024
In this study, we developed a lightweight and rapid convolutional neural network (CNN) architecture for chest X-ray images; it primarily consists of a redesigned feature extraction (FE) module and multiscale feature (MF) module and validated using pu...
CorLabelNet: a comprehensive framework for multi-label chest X-ray image classification with correlation guided discriminant feature learning and oversampling.
Medical & biological engineering & computing
Nov 29, 2024
Recent advancements in deep learning techniques have significantly improved multi-label chest X-ray (CXR) image classification for clinical diagnosis. However, most previous studies neither effectively learn label correlations nor take full advantage...
Extraction and evaluation of features of preterm patent ductus arteriosus in chest X-ray images using deep learning.
Scientific reports
Nov 26, 2024
Echocardiography is the gold standard of diagnosis and evaluation of patent ductus arteriosus (PDA), a common condition among preterm infants that can cause hemodynamic abnormalities and increased mortality rates, but this technique requires a skille...
Effect of Artificial Intelligence as a Second Reader on the Lung Nodule Detection and Localization Accuracy of Radiologists and Non-radiology Physicians in Chest Radiographs: A Multicenter Reader Study.
Academic radiology
Nov 25, 2024
RATIONALE AND OBJECTIVES: Missed nodules in chest radiographs (CXRs) are common occurrences. We assessed the effect of artificial intelligence (AI) as a second reader on the accuracy of radiologists and non-radiology physicians in lung nodule detecti...
Aged
Radiographic Image Interpretation, Computer-Assisted
Sensitivity and Specificity
Observer Variation
Male
Radiography, Thoracic
Solitary Pulmonary Nodule
Radiologists
Tomography, X-Ray Computed
Humans
Female
Middle Aged
Artificial Intelligence
Reproducibility of Results
Lung Neoplasms
Retrospective Studies
Attention-based multi-residual network for lung segmentation in diseased lungs with custom data augmentation.
Scientific reports
Nov 22, 2024
Lung disease analysis in chest X-rays (CXR) using deep learning presents significant challenges due to the wide variation in lung appearance caused by disease progression and differing X-ray settings. While deep learning models have shown remarkable ...
Impact of Deep Learning-Based Computer-Aided Detection and Electronic Notification System for Pneumothorax on Time to Treatment: Clinical Implementation.
Journal of the American College of Radiology : JACR
Nov 19, 2024
OBJECTIVE: To assess whether the implementation of deep learning (DL) computer-aided detection (CAD) that screens for suspected pneumothorax (PTX) on chest radiography (CXR) combined with an electronic notification system (ENS) that simultaneously al...
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