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   Articles with "supervised denoising" as a keyword



Self‐supervised denoising diffusion probabilistic models for abdominal DW‐MRI

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recommendations! Published in 2025 at "Magnetic Resonance in Medicine"

DOI: 10.1002/mrm.30536

Abstract: To improve the quality of abdominal diffusion‐weighted MR images (DW‐MRI) when acquired using single‐repetition (NEX = 1) protocols, and thereby increase apparent diffusion coefficient (ADC) map accuracy and lesion conspicuity at high b‐values. We aim… read more here.

Keywords: probabilistic models; self supervised; diffusion probabilistic; supervised denoising ... See more keywords

Supervised Denoising for Extreme Low-Light Raw Videos

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recommendations! Published in 2025 at "IEEE Transactions on Circuits and Systems for Video Technology"

DOI: 10.1109/tcsvt.2025.3572547

Abstract: Denoising is a critical task in computer vision tasks, especially in challenging environments like extreme low-light conditions. However, the lack of research on denoising raw video in extreme low-light environments is notable, as is the… read more here.

Keywords: raw videos; low light; supervised denoising; extreme low ... See more keywords

Semi-Supervised CT Denoising via Text-Guided Mamba Diffusion Models

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recommendations! Published in 2025 at "IEEE Transactions on Instrumentation and Measurement"

DOI: 10.1109/tim.2025.3552389

Abstract: Low-dose computed tomography (CT) reduces patient radiation exposure, yet it introduces noise and artifacts that can impair diagnostics. Recent supervised methods, particularly the diffusion method, have effectively minimized image smoothing while preserving details. However, iterative… read more here.

Keywords: low dose; supervised denoising; text guided; semi supervised ... See more keywords

Self-supervised denoising of Nyquist-sampled volumetric images via deep learning

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recommendations! Published in 2023 at "Journal of Medical Imaging"

DOI: 10.1117/1.jmi.10.2.024005

Abstract: Abstract. Purpose Deep learning has demonstrated excellent performance enhancing noisy or degraded biomedical images. However, many of these models require access to a noise-free version of the images to provide supervision during training, which limits… read more here.

Keywords: supervised denoising; self supervised; deep learning; denoising nyquist ... See more keywords