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Quantitative CT textures of the lung help assess COPD severity
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Images show lung ultrasound findings of major pleuro-pulmonary pathologies. (a) Pleural effusion; (b) Pneumonia; (c) Bronchopneumonia; (d) Acute pulmonary edema; (e) Chronic obstructive pulmonary disease exacerbation; (f) Pleuropulmonary tumors; (g) Acute respiratory distress syndrome.
Lung POCUS helps diagnose dyspnea in emergency departments
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Quantitative CT textures of the lung help assess COPD severity
By Kate Madden Yee
Quantitative CT can capture lung inflammation patterns to assess the severity of chronic obstructive pulmonary disease (COPD).
April 23, 2025
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Medtech industry and health leaders from big tech have introduced a new AI Policy Roadmap.
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ACS: Breast cancer screening rates have recovered post-COVID
By Kate Madden Yee
Rates of up-to-date breast cancer screening have recovered after declining during the COVID-19 pandemic.
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Lung POCUS helps diagnose dyspnea in emergency departments
By Amerigo Allegretto
Point-of-care lung ultrasound may be useful in the emergency department for diagnosing dyspnea.
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Images show lung ultrasound findings of major pleuro-pulmonary pathologies. (a) Pleural effusion; (b) Pneumonia; (c) Bronchopneumonia; (d) Acute pulmonary edema; (e) Chronic obstructive pulmonary disease exacerbation; (f) Pleuropulmonary tumors; (g) Acute respiratory distress syndrome.
MRI tool segments over 60 abdominal organs, structures
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Figure: Improved image quality with a generative adversarial network architecture for low- to high-field-strength image translation, called LowGAN. (A–C) Top: High-field-strength (3-T) and low-field-strength (64-mT) images and LowGAN outputs for a single participant across (A) fluid-attenuated inversion recovery (FLAIR), (B) T1-weighted (T1w), and (C) T2-weighted (T2w) contrasts. Bottom: Graphs demonstrate the structural similarity index (SSIM), peak signal-to-noise ratio (PSNR), normalized cross-correlation (NCC), and feature similarity index (FSIM) between high field strength and low field strength (64-mT) and high field strength and LowGAN outputs. a.u. = arbitrary units.****p ≤ 0.0001. Images and caption courtesy of Radiology and the RSNA.
Machine learning standardizes bone tumor grading on MRI, CT
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