Medical Image Denoising
6 papers with code • 6 benchmarks • 2 datasets
Benchmarks
These leaderboards are used to track progress in Medical Image Denoising
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BCNB
Human Protein Atlas
Most implemented papers
Medical image denoising using convolutional denoising autoencoders
adam-mah/Medical-Image-Denoising
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Image denoising is an important pre-processing step in medical image analysis.
Content-Noise Complementary Learning for Medical Image Denoising
gengmufeng/CNCL-denoising
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IEEE Transactions on Medical Imaging 2022
In this study, we propose a simple yet effective strategy, the content-noise complementary learning (CNCL) strategy, in which two deep learning predictors are used to learn the respective content and noise of the image dataset complementarily.
Uncertainty Estimation in Medical Image Denoising with Bayesian Deep Image Prior
mlaves/uncertainty-deep-image-prior
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We use a randomly initialized convolutional network as parameterization of the reconstructed image and perform gradient descent to match the observation, which is known as deep image prior.
Learning Medical Image Denoising with Deep Dynamic Residual Attention Network
Image denoising performs a prominent role in medical image analysis.
Transformers in Medical Imaging: A Survey
fahadshamshad/awesome-transformers-in-medical-imaging
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Following unprecedented success on the natural language tasks, Transformers have been successfully applied to several computer vision problems, achieving state-of-the-art results and prompting researchers to reconsider the supremacy of convolutional neural networks (CNNs) as {de facto} operators.
Adversarial Distortion Learning for Medical Image Denoising
mogvision/adl
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The proposed ADL consists of two auto-encoders: a denoiser and a discriminator.
