DeScoD-ECG: Deep Score-Based Diffusion Model for ECG Baseline Wander and Noise Removal. [PDF]
IEEE J Biomed Health Inform, 2022 Objective: Electrocardiogram (ECG) signals commonly suffer noise interference, such as baseline wander. High-quality and high-fidelity reconstruction of the ECG signals is of great significance to diagnosing cardiovascular diseases. Therefore, this paper
Li H, Ditzler G, Roveda J, Li A.
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Image Noise Removal in Ultrasound Breast Images Based on Hybrid Deep Learning Technique. [PDF]
Sensors (Basel), 2023 Rapid improvements in ultrasound imaging technology have made it much more useful for screening and diagnosing breast problems. Local-speckle-noise destruction in ultrasound breast images may impair image quality and impact observation and diagnosis.
Vimala BB +6 more
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An Adaptive ECG Noise Removal Process Based on Empirical Mode Decomposition (EMD). [PDF]
Contrast Media Mol Imaging, 2022 The electrocardiogram (ECG) is a generally used instrument for examining cardiac disorders. For proper interpretation of cardiac illnesses, a noise-free ECG is often preferred. ECG signals, on the other hand, are suffering from numerous noises throughout
Hussein AF +3 more
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HOS-based image sequence noise removal [PDF]
IEEE Transactions on Image Processing, 2006 In this paper, a new spatiotemporal filtering scheme is described for noise reduction in video sequences. For this purpose, the scheme processes each group of three consecutive sequence frames in two steps: 1) estimate motion between frames and 2) use motion vectors to get the final denoised current frame.
El Hassouni, M. +2 more
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Invertible Denoising Network: A Light Solution for Real Noise Removal [PDF]
Computer Vision and Pattern Recognition, 2021 Invertible networks have various benefits for image de-noising since they are lightweight, information-lossless, and memory-saving during back-propagation. However, applying invertible models to remove noise is challenging because the input is noisy, and
Yang Liu +6 more
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LinkNet-B7: Noise Removal and Lesion Segmentation in Images of Skin Cancer
Mathematics, 2022 Skin cancer is common nowadays. Early diagnosis of skin cancer is essential to increase patients’ survival rate. In addition to traditional methods, computer-aided diagnosis is used in diagnosis of skin cancer.
Cihan Akyel, Nursal Arıcı
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Training a neural network for Gibbs and noise removal in diffusion MRI. [PDF]
Magn Reson Med, 2021 To develop and evaluate a neural network–based method for Gibbs artifact and noise removal.
Muckley MJ +9 more
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Fast Noise Removal in Hyperspectral Images via Representative Coefficient Total Variation [PDF]
IEEE Transactions on Geoscience and Remote Sensing, 2022 Mining structural priors in data is a widely recognized technique for hyperspectral image (HSI) denoising tasks, whose typical ways include model-based methods and data-based methods.
Jiangjun Peng +5 more
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Deep Learning Based Switching Filter for Impulsive Noise Removal in Color Images. [PDF]
Sensors (Basel), 2020 Noise reduction is one of the most important and still active research topics in low-level image processing due to its high impact on object detection and scene understanding for computer vision systems.
Radlak K, Malinski L, Smolka B.
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Model-based physiological noise removal in fast fMRI. [PDF]
Neuroimage, 2020 Agrawal U, Brown EN, Lewis LD.
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