AIMC Topic: Lung
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Generative Adversarial Networks With Radiomics Supervision for Lung Lesion Generation.
IEEE transactions on bio-medical engineering
Jan 15, 2025
Data-driven methods for lesion generation are quickly emerging due to the need for realistic imaging targets for image quality assessment and virtual clinical trials. We proposed a generative adversarial network (GAN) architecture for conditional gen...
Sparse keypoint segmentation of lung fissures: efficient geometric deep learning for abstracting volumetric images.
International journal of computer assisted radiology and surgery
Jan 7, 2025
PURPOSE: Lung fissure segmentation on CT images often relies on 3D convolutional neural networks (CNNs). However, 3D-CNNs are inefficient for detecting thin structures like the fissures, which make up a tiny fraction of the entire image volume. We pr...
Deciphering the cellular and molecular landscape of pulmonary fibrosis through single-cell sequencing and machine learning.
Journal of translational medicine
Jan 2, 2025
Pulmonary fibrosis is characterized by progressive lung scarring, leading to a decline in lung function and an increase in morbidity and mortality. This study leverages single-cell sequencing and machine learning to unravel the complex cellular and m...
A New Benchmark: Clinical Uncertainty and Severity Aware Labeled Chest X-Ray Images With Multi-Relationship Graph Learning.
IEEE transactions on medical imaging
Jan 2, 2025
Chest radiography, commonly known as CXR, is frequently utilized in clinical settings to detect cardiopulmonary conditions. However, even seasoned radiologists might offer different evaluations regarding the seriousness and uncertainty associated wit...
Weakly Supervised Object Detection in Chest X-Rays With Differentiable ROI Proposal Networks and Soft ROI Pooling.
IEEE transactions on medical imaging
Jan 2, 2025
Weakly supervised object detection (WSup-OD) increases the usefulness and interpretability of image classification algorithms without requiring additional supervision. The successes of multiple instance learning in this task for natural images, howev...
Machine learning identifies remodeling patterns in human lung extracellular matrix.
Acta biomaterialia
Dec 31, 2024
Organ function depends on the three-dimensional integrity of the extracellular matrix (ECM). The structure resulting from the location and association of ECM components is a central regulator of cell behavior, but a dearth of matrix-specific analysis...
Sub-millimeter fiberscopic robot with integrated maneuvering, imaging, and biomedical operation abilities.
Nature communications
Dec 30, 2024
Small-scale continuum robots hold promise for interventional diagnosis and treatment, yet existing models struggle to achieve small size, precise steering, and visualized functional treatment simultaneously, termed an "impossible trinity". This study...
Noninvasive estimation of PaCO from volumetric capnography in animals with injured lungs: an Artificial Intelligence approach.
Journal of clinical monitoring and computing
Dec 26, 2024
To investigate the feasibility of non-invasively estimating the arterial partial pressure of carbon dioxide (PaCO) using a computational Adaptive Neuro-Fuzzy Inference System (ANFIS) model fed by noninvasive volumetric capnography (VCap) parameters. ...
Improving functional correlation of quantification of interstitial lung disease by reducing the vendor difference of CT using generative adversarial network (GAN) style conversion.
European journal of radiology
Dec 22, 2024
OBJECTIVE: To assess whether CT style conversion between different CT vendors using a routable generative adversarial network (RouteGAN) could minimize variation in ILD quantification, resulting in improved functional correlation of quantitative CT (...
Lung
Humans
Deep Learning
Idiopathic Pulmonary Fibrosis
Female
Aged
Retrospective Studies
Reproducibility of Results
Male
Tomography, X-Ray Computed
Middle Aged
Generative Adversarial Networks
Radiographic Image Interpretation, Computer-Assisted
Lung Diseases, Interstitial
Respiratory Function Tests
Automated measurement of cardiothoracic ratio based on semantic segmentation integration model using deep learning.
Medical & biological engineering & computing
Dec 21, 2024
The objective of this study is to investigate the efficacy of the semantic segmentation model in predicting cardiothoracic ratio (CTR) and heart enlargement and compare its consistency with the reference standard. A total of 650 consecutive chest rad...
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