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Published in 2025 at "Scientific Reports"
DOI: 10.1038/s41598-025-25755-1
Abstract: Manual selection of optimal frames from kidney ultrasound videos is a time-consuming and subjective process that can introduce variability into clinical assessments. This study presents a fully automated deep learning–based framework designed to identify the…
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Keywords:
deep learning;
frame selection;
kidney ultrasound;
selection ... See more keywords
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Published in 2022 at "IEEE Journal of Biomedical and Health Informatics"
DOI: 10.1109/jbhi.2022.3152625
Abstract: Endobronchial ultrasound (EBUS) elastography videos have shown great potential to supplement intrathoracic lymph node diagnosis. However, it is laborious and subjective for the specialists to select the representative frames from the tedious videos and make…
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Keywords:
elastography;
elastography videos;
diagnosis;
automatic representative ... See more keywords
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Published in 2022 at "IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control"
DOI: 10.1109/tuffc.2022.3149287
Abstract: Thermal strain imaging (TSI) uses echo shifts in ultrasonic B-scan images to estimate changes in temperature which is of great values for thermotherapies. However, for in vivo applications, it is difficult to overcome the artifacts…
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Keywords:
frame selection;
exhalation inhalation;
strain imaging;
inhalation phases ... See more keywords
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Published in 2024 at "Applied Sciences"
DOI: 10.3390/app14219947
Abstract: Graph neural networks (GNNs) are extensively utilized to capture the spatial–temporal relationships among human body parts for skeleton-based action recognition. However, due to the inefficient information propagation caused by redundant sampling of video frames in…
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Keywords:
frame selection;
action recognition;
key frame;