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Regional Image Quality Scoring for 2-D Echocardiography Using Deep Learning.
Ultrasound Med Biol
January 2025
Department of Circulation and Medical Imaging, Norwegian University of Science and Technology - NTNU, Trondheim, Norway; Health Research, SINTEF, Trondheim, Norway.
Objective: To develop and compare methods to automatically estimate regional ultrasound image quality for echocardiography separate from view correctness.
Methods: Three methods for estimating image quality were developed: (i) classic pixel-based metric: the generalized contrast-to-noise ratio (gCNR), computed on myocardial segments (region of interest) and left ventricle lumen (background), extracted by a U-Net segmentation model; (ii) local image coherence: the average local coherence as predicted by a U-Net model that predicts image coherence from B-mode ultrasound images at the pixel level; (iii) deep convolutional network: an end-to-end deep-learning model that predicts the quality of each region in the image directly. These methods were evaluated against manual regional quality annotations provided by three experienced cardiologists.
Performance of an Electronic Health Record-Based Automated Pulmonary Embolism Severity Index Score Calculator: Cohort Study in the Emergency Department.
JMIR Med Inform
January 2025
Department of Emergency Medicine, University of Michigan, Ann Arbor, MI, United States.
Background: Studies suggest that less than 4% of patients with pulmonary embolisms (PEs) are managed in the outpatient setting. Strong evidence and multiple guidelines support the use of the Pulmonary Embolism Severity Index (PESI) for the identification of acute PE patients appropriate for outpatient management. However, calculating the PESI score can be inconvenient in a busy emergency department (ED).
View Article and Find Full Text PDFQuantifying Knee-Adjacent Subcutaneous Fat in the Entire OAI Baseline Dataset - Associations with Cartilage MRI T, Thickness and Pain, Independent of BMI.
Osteoarthritis Cartilage
January 2025
Department of Radiology and Biomedical Imaging, University of California, San Francisco.
Objective: Knee-adjacent subcutaneous fat (kaSCF) has emerged as a potential biomarker and risk factor for OA progression. This study aims to develop an AI-based tool for the automatic segmentation of kaSCF thickness and evaluate the cross-sectional associations between kaSCF, cartilage thickness, MRI-based cartilage T relaxation time, knee pain, and muscle strength independent of BMI.
Design: Baseline 3.
Unveiling significant regrowth and potential risk of nontuberculous mycobacteria in hospital water supply system.
Water Res
January 2025
Department of Urban Engineering, School of Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo, Tokyo 113-8656, Japan; Research Center for Advanced Science and Technology, The University of Tokyo, 4-6-1, Komaba, Meguro, Tokyo 153-8904, Japan. Electronic address:
The health burden of waterborne nontuberculous mycobacteria (NTM) is a rising concern. While the water supply systems can serve as a potential reservoir for NTM, their abundance, diversity, and transmission pathways remain unknown. This study aimed to characterize the prevalence and regrowth of NTM in building water supply system in a hospital where many M.
View Article and Find Full Text PDFSensitivity-enhanced hydrogel digital RT-LAMP with in situ enrichment and interfacial reaction for norovirus quantification in food and water.
J Hazard Mater
January 2025
College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China. Electronic address:
Low levels of human norovirus (HuNoV) in food and environment present challenges for nucleic acid detection. This study reported an evaporation-enhanced hydrogel digital reverse transcription loop-mediated isothermal amplification (HD RT-LAMP) with interfacial enzymatic reaction for sensitive HuNoV quantification in food and water. By drying samples on a chamber array chip, HuNoV particles were enriched in situ.
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