Volumetric non-local-means based speckle reduction for optical coherence tomography. [PDF]
Biomed Opt Express, 2018 We present a novel tomographic non-local-means based despeckling technique, TNode, for optical coherence tomography. TNode is built upon a weighting similarity criterion derived for speckle in a three-dimensional similarity window.
Carlos Cuartas-Vélez +3 more
semanticscholar +3 more sources
De-Speckling Breast Cancer Ultrasound Images Using a Rotationally Invariant Block Matching Based Non-Local Means (RIBM-NLM) Method [PDF]
Diagnostics, 2022 The ultrasonic technique is an indispensable imaging modality for diagnosis of breast cancer in young women due to its ability in efficiently capturing the tissue properties, and decreasing nega-tive recognition rate thereby avoiding non-essential ...
Gelan Ayana +4 more
doaj +3 more sources
Auto-segmentation of head and neck tumors in positron emission tomography images using non-local means and morphological frameworks [PDF]
Pol J Radiol, 2023 Purpose Accurately segmenting head and neck cancer (HNC) tumors in medical images is crucial for effective treatment planning. However, current methods for HNC segmentation are limited in their accuracy and efficiency. The present study aimed to design a
Sahel Heydarheydari +2 more
semanticscholar +2 more sources
Automatic Muscle Artifacts Identification and Removal from Single-Channel EEG Using Wavelet Transform with Meta-Heuristically Optimized Non-Local Means Filter [PDF]
Sensors (Basel), 2022 Electroencephalogram (EEG) signals may get easily contaminated by muscle artifacts, which may lead to wrong interpretation in the brain–computer interface (BCI) system as well as in various medical diagnoses. The main objective of this paper is to remove
Souvik Phadikar +3 more
semanticscholar +2 more sources
Voxel-based partial volume correction of PET images via subtle MRI guided non-local means regularization [PDF]
Phys Med, 2021 Purpose: Positron emission tomography (PET) images tend to be significantly degraded by the partial volume effect (PVE) resulting from the limited spatial resolution of the reconstructed images. Our purpose is to propose a partial volume correction (PVC)
Yuanyuan Gao +5 more
semanticscholar +2 more sources
Application of Fast Non-Local Means Algorithm for Noise Reduction Using Separable Color Channels in Light Microscopy Images [PDF]
Int J Environ Res Public Health, 2021 The purpose of this study is to evaluate the various control parameters of a modeled fast non-local means (FNLM) noise reduction algorithm which can separate color channels in light microscopy (LM) images. To achieve this objective, the tendency of image
S. Kang, Ji-Youn Kim
semanticscholar +2 more sources
An enhanced adaptive non-local means algorithm for Rician noise reduction in magnetic resonance brain images [PDF]
BMC Med Imaging, 2020 BackgroundThe Rician noise formed in magnetic resonance (MR) imaging greatly reduced the accuracy and reliability of subsequent analysis, and most of the existing denoising methods are suitable for Gaussian noise rather than Rician noise. Aiming to solve
Kaixin Chen +5 more
semanticscholar +2 more sources
Effectiveness of Non-Local Means Algorithm with an Industrial 3 MeV LINAC High-Energy X-ray System for Non-Destructive Testing [PDF]
Sensors (Basel), 2020 Industrial high-energy X-ray imaging systems are widely used for non-destructive testing (NDT) to detect defects in the internal structure of objects.
Kyuseok Kim, Jaegu Choi, Youngjin Lee
semanticscholar +2 more sources
Tensor decomposition and non-local means based spectral CT image denoising [PDF]
J Xray Sci Technol, 2019 BACKGROUND As one type of the state-of-the-art detectors, photon counting detectors are used in spectral computed tomography (CT) to classify the received photons into several energy channels and generate multichannel projections simultaneously. However,
Yanbo Zhang +2 more
semanticscholar +2 more sources
Non-local means denoising of dynamic PET images. [PDF]
PLoS ONE, 2013 ObjectiveDynamic positron emission tomography (PET), which reveals information about both the spatial distribution and temporal kinetics of a radiotracer, enables quantitative interpretation of PET data.
Joyita Dutta +2 more
doaj +2 more sources