RADAR: Raman Spectral Analysis Using Deep Learning for Artifact Removal
Sign Up to like & getrecommendations! Published in 2025 at "Advanced Optical Materials"
DOI: 10.1002/adom.202500736
Abstract: Raman spectroscopy is a non‐destructive analytical technique that reveals molecular vibrations, enabling precise identification of chemical compounds and material properties. Its spatial resolution and compatibility with microscopic imaging allow for high‐resolution chemical mapping of heterogeneous… read more here.
Keywords: deep learning; spectroscopy; radar raman; raman spectral ... See more keywords
EEG Artifact Removal in TMS Studies of Cortical Speech Areas
Sign Up to like & getrecommendations! Published in 2019 at "Brain Topography"
DOI: 10.1007/s10548-019-00724-w
Abstract: The combination of transcranial magnetic stimulation (TMS) and electroencephalography (EEG) is commonly applied for studying the effective connectivity of neuronal circuits. The stimulation excites neurons, and the resulting TMS-evoked potentials (TEPs) are recorded with EEG.… read more here.
Keywords: speech areas; artifact removal; muscle; tms ... See more keywords
Artifact Removal from Data Generated by Nonlinear Systems: Heart Rate Estimation from Blood Volume Pulse Signal
Sign Up to like & getrecommendations! Published in 2019 at "Industrial & Engineering Chemistry Research"
DOI: 10.1021/acs.iecr.9b04824
Abstract: Artifacts are disturbances affecting a measured signal that are not originating from the process itself. This paper addresses the problem of heart rate (HR) monitoring from a photoplethysmography (PPG) sensor, where artifacts caused by body… read more here.
Keywords: artifact removal; heart rate; heart; signal ... See more keywords
A novel EEG artifact removal algorithm based on an advanced attention mechanism
Sign Up to like & getrecommendations! Published in 2025 at "Scientific Reports"
DOI: 10.1038/s41598-025-98653-1
Abstract: EEG is widely applied in emotion recognition, brain disease detection, and other fields due to its high temporal resolution and non-invasiveness. However, artifact removal remains a crucial issue in EEG signal processing. Recently, with the… read more here.
Keywords: removal; eeg artifact; artifact removal; attention mechanism ... See more keywords
Iterative image-domain ring artifact removal in cone-beam CT.
Sign Up to like & getrecommendations! Published in 2017 at "Physics in medicine and biology"
DOI: 10.1088/1361-6560/aa7017
Abstract: Ring artifacts in cone beam computed tomography (CBCT) images are caused by pixel gain variations using flat-panel detectors, and may lead to structured non-uniformities and deterioration of image quality. The purpose of this study is… read more here.
Keywords: artifact removal; image; ring artifacts; ring artifact ... See more keywords
Integration Design of Portable ECG Signal Acquisition With Deep-Learning Based Electrode Motion Artifact Removal on an Embedded System
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3178847
Abstract: For long-term electrocardiogram (ECG) signal monitoring, a portable and small size acquisition device with Bluetooth low energy (BLE) communication is designed and integrated with a Nvidia Jetson Xavier NX for realizing the electrode motion artifact… read more here.
Keywords: motion artifact; artifact removal; electrode motion; ecg signal ... See more keywords
DPA-HairNet: A Dual Encoder Attention Based Network for Hair Artifact Removal in Dermoscopic Images
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Access"
DOI: 10.1109/access.2025.3585353
Abstract: Hair artifacts in dermoscopic images significantly hinder the accurate diagnosis of melanoma and other skin conditions by obscuring critical lesion details. To address this challenge, we introduce DPA-HairNet, a novel Dual Encoder Attention-Based Network designed… read more here.
Keywords: dual encoder; attention; hair artifact; artifact removal ... See more keywords
PIE-ARNet: Prior Image Enhanced Artifact Removal Network for Limited-Angle DECT
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Instrumentation and Measurement"
DOI: 10.1109/tim.2022.3221772
Abstract: Dual-energy computed tomography (DECT) is of great clinical significance because it can simultaneously visualize the internal structure of the scanned object and provide material-specific information. DECT obtains two attenuation measurements of the same object at… read more here.
Keywords: artifact removal; dect; pie arnet; prior image ... See more keywords
Adaptive Single-Channel EEG Artifact Removal With Applications to Clinical Monitoring
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Neural Systems and Rehabilitation Engineering"
DOI: 10.1109/tnsre.2022.3147072
Abstract: Electroencephalography (EEG) has become very common in clinical practice due to its relatively low cost, ease of installation, non-invasiveness, and good temporal resolution. Portable EEG devices are increasingly popular in clinical monitoring applications such as… read more here.
Keywords: method; single channel; channel eeg; clinical monitoring ... See more keywords
A Real-Time Artifact Removal System for Closed-Loop Deep-Brain Stimulation
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Transactions on Neural Systems and Rehabilitation Engineering"
DOI: 10.1109/tnsre.2025.3597916
Abstract: This paper presents a novel real-time signal processing method for removing local field potential (LFP) artifacts during deep-brain stimulation (DBS). Real-time artifact removal is essential for closed-loop DBS systems, as they rely on real-time, artifact-free… read more here.
Keywords: method; real time; time; artifact removal ... See more keywords
Deep learning-based motion artifact removal in functional near-infrared spectroscopy
Sign Up to like & getrecommendations! Published in 2022 at "Neurophotonics"
DOI: 10.1117/1.nph.9.4.041406
Abstract: Abstract. Significance: Functional near-infrared spectroscopy (fNIRS), a well-established neuroimaging technique, enables monitoring cortical activation while subjects are unconstrained. However, motion artifact is a common type of noise that can hamper the interpretation of fNIRS data.… read more here.
Keywords: spectroscopy; motion; motion artifact; deep learning ... See more keywords