AIMC Topic: Lung

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Deep Learning-Based Computed Tomography Imaging to Diagnose the Lung Nodule and Treatment Effect of Radiofrequency Ablation.

Journal of healthcare engineering Oct 20, 2021
This study aimed to detect and diagnose the lung nodules as early as possible to effectively treat them, thereby reducing the burden on the medical system and patients. A lung computed tomography (CT) image segmentation algorithm was constructed base...
Lung Deep Learning Lung Neoplasms Humans Tomography, X-Ray Computed Radiographic Image Interpretation, Computer-Assisted Radiofrequency Ablation
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Deep learning for lung disease segmentation on CT: Which reconstruction kernel should be used?

Diagnostic and interventional imaging Oct 19, 2021
PURPOSE: The purpose of this study was to determine whether a single reconstruction kernel or both high and low frequency kernels should be used for training deep learning models for the segmentation of diffuse lung disease on chest computed tomograp...
COVID-19 Tomography, X-Ray Computed SARS-CoV-2 Humans Lung Deep Learning Image Processing, Computer-Assisted
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Few-shot learning for deformable image registration in 4DCT images.

The British journal of radiology Oct 18, 2021
OBJECTIVES: To develop a rapid and accurate 4D deformable image registration (DIR) approach for online adaptive radiotherapy.
Respiration Exhalation Inhalation Radiotherapy, Image-Guided Four-Dimensional Computed Tomography Deep Learning Time Factors Radiotherapy Planning, Computer-Assisted Humans Lung
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Weakly supervised learning for classification of lung cytological images using attention-based multiple instance learning.

Scientific reports Oct 13, 2021
In cytological examination, suspicious cells are evaluated regarding malignancy and cancer type. To assist this, we previously proposed an automated method based on supervised learning that classifies cells in lung cytological images as benign or mal...
Carcinoma, Squamous Cell Reproducibility of Results Lung Humans Neural Networks, Computer Retrospective Studies Image Interpretation, Computer-Assisted Medical Informatics Pattern Recognition, Automated Thorax Small Cell Lung Carcinoma Chromatin Lung Neoplasms Adenocarcinoma Deep Learning Supervised Machine Learning Image Processing, Computer-Assisted
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Content-based Image Retrieval by Using Deep Learning for Interstitial Lung Disease Diagnosis with Chest CT.

Radiology Oct 12, 2021
Background Evaluation of interstitial lung disease (ILD) at CT is a challenging task that requires experience and is subject to substantial interreader variability. Purpose To investigate whether a proposed content-based image retrieval (CBIR) of sim...
Female Reproducibility of Results Male Humans Retrospective Studies Diagnosis, Differential Tomography, X-Ray Computed Middle Aged Lung Deep Learning Radiographic Image Interpretation, Computer-Assisted Lung Diseases, Interstitial
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COVID-19 detection from lung CT-Scans using a fuzzy integral-based CNN ensemble.

Computers in biology and medicine Oct 1, 2021
The COVID-19 pandemic has collapsed the public healthcare systems, along with severely damaging the economy of the world. The SARS-CoV-2 virus also known as the coronavirus, led to community spread, causing the death of more than a million people wor...
SARS-CoV-2 Lung Deep Learning Pandemics COVID-19 Tomography, X-Ray Computed Humans
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Interpretability-Driven Sample Selection Using Self Supervised Learning for Disease Classification and Segmentation.

IEEE transactions on medical imaging Sep 30, 2021
In supervised learning for medical image analysis, sample selection methodologies are fundamental to attain optimum system performance promptly and with minimal expert interactions (e.g. label querying in an active learning setup). In this article we...
Supervised Machine Learning Uncertainty Lung
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Diagnostic test accuracy of artificial intelligence analysis of cross-sectional imaging in pulmonary hypertension: a systematic literature review.

The British journal of radiology Sep 29, 2021
OBJECTIVES: To undertake the first systematic review examining the performance of artificial intelligence (AI) applied to cross-sectional imaging for the diagnosis of acquired pulmonary arterial hypertension (PAH).
Humans Sensitivity and Specificity Image Interpretation, Computer-Assisted Lung Hypertension, Pulmonary Magnetic Resonance Imaging Artificial Intelligence Tomography, X-Ray Computed Reproducibility of Results
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Dynamic memory to alleviate catastrophic forgetting in continual learning with medical imaging.

Nature communications Sep 28, 2021
Medical imaging is a central part of clinical diagnosis and treatment guidance. Machine learning has increasingly gained relevance because it captures features of disease and treatment response that are relevant for therapeutic decision-making. In cl...
Diagnostic Imaging Neural Networks, Computer Learning Memory Lung Machine Learning Tomography, X-Ray Computed Humans
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A Novel Medical Image Denoising Method Based on Conditional Generative Adversarial Network.

Computational and mathematical methods in medicine Sep 28, 2021
Medical image quality is highly relative to clinical diagnosis and treatment, leading to a popular research topic of medical image denoising. Image denoising based on deep learning methods has attracted considerable attention owing to its excellent a...
Lung Humans Deep Learning Computational Biology Image Interpretation, Computer-Assisted Neural Networks, Computer Computer Simulation Signal-To-Noise Ratio Algorithms Tomography, X-Ray Computed Databases, Factual
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