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largest decrease » larger decrease (Expand Search), marked decrease (Expand Search)
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teer decrease » mean decrease (Expand Search), greater decrease (Expand Search)
largest decrease » larger decrease (Expand Search), marked decrease (Expand Search)
values decrease » values increased (Expand Search)
linear decrease » linear increase (Expand Search)
teer decrease » mean decrease (Expand Search), greater decrease (Expand Search)
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Video 1_The clinical application value of mixed reality in robotic laparoscopic partial nephrectomy.mp4
Published 2024“…All patients underwent mid-abdominal CT plain scans and enhancements. The MR group utilized three-dimensional reconstruction of CT data and employed 3D tablets and HoloLens glasses for preoperative discussions, surgical planning, and intraoperative guidance. …”
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Evaluation results.
Published 2024“…<div><p>Spectral Photon Counting Computed Tomography (SPCCT), a ground-breaking development in CT technology, has immense potential to address the persistent problem of metal artefacts in CT images. …”
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Dataset with steel insert.
Published 2024“…<div><p>Spectral Photon Counting Computed Tomography (SPCCT), a ground-breaking development in CT technology, has immense potential to address the persistent problem of metal artefacts in CT images. …”
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Reference dataset.
Published 2024“…<div><p>Spectral Photon Counting Computed Tomography (SPCCT), a ground-breaking development in CT technology, has immense potential to address the persistent problem of metal artefacts in CT images. …”
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Dataset with aluminium insert.
Published 2024“…<div><p>Spectral Photon Counting Computed Tomography (SPCCT), a ground-breaking development in CT technology, has immense potential to address the persistent problem of metal artefacts in CT images. …”
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Multiple linear regression analysis results.
Published 2025“…Cohesiveness varied without a clear linear trend, showing significant changes at specific IDDSI levels for meats, grains, and tubers (<i>p</i>≤0.05). …”
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A Locally Linear Dynamic Strategy for Manifold Learning.
Published 2025“…For 10-30% noise, where the Hebbian network employs a local linear transform, learning selectively increases signal direction alignment (blue) while simultaneously decreasing noise direction alignment (orange). …”
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