Add to ORKGWeaddress suppression of artifacts in NIRS time-series imaging. We report a fast algorithm, combining sparse optimization and filtering, that jointly estimates two explicitly modeled artifact types: transient disruptions and step discontinuities
Near-infrared spectroscopy (NIRS) is susceptible to signal artifacts caused by relative motion betwe...
This report presents an algorithm for removing artifacts from EEG signal, which is based on the meth...
Abstract. A novel reconstruction technique, called Wiener Filtered Recon-struction Technique (WIRT),...
We address suppression of artifacts in NIRS time-series imaging. We report a fast algorithm, combini...
Abstract: We address suppression of artifacts in NIRS time-series imaging. We report a fast algorith...
Abstract—This paper addresses the suppression of transient artifacts in signals, e.g., biomedical ti...
Near-infrared spectroscopy (NIRS) enables the non-invasive measurement of changes in hemodynamics an...
Background: Muscle artifacts and electrode noise are an obstacle to interpretation of EEG and other ...
As near-infrared spectroscopy (NIRS) broadens its application area to different age and disease grou...
Motion artifact contamination in near-infrared spectroscopy (NIRS) data has become an important chal...
Abstract—This paper seeks to combine linear time-invariant (LTI) filtering and sparsity-based denois...
One of the most promising alternative imaging modalities for breast cancer detection involved the us...
This chapter studies the problem of time-series classification and presents an overview of recent de...
In this work we analyze the problem of the ghosting artifacts coming out from non-uniformity correct...
The LMS-based adaptive non-uniformity correction (NUC) technique, known in the literature as Scribne...
Near-infrared spectroscopy (NIRS) is susceptible to signal artifacts caused by relative motion betwe...
This report presents an algorithm for removing artifacts from EEG signal, which is based on the meth...
Abstract. A novel reconstruction technique, called Wiener Filtered Recon-struction Technique (WIRT),...
We address suppression of artifacts in NIRS time-series imaging. We report a fast algorithm, combini...
Abstract: We address suppression of artifacts in NIRS time-series imaging. We report a fast algorith...
Abstract—This paper addresses the suppression of transient artifacts in signals, e.g., biomedical ti...
Near-infrared spectroscopy (NIRS) enables the non-invasive measurement of changes in hemodynamics an...
Background: Muscle artifacts and electrode noise are an obstacle to interpretation of EEG and other ...
As near-infrared spectroscopy (NIRS) broadens its application area to different age and disease grou...
Motion artifact contamination in near-infrared spectroscopy (NIRS) data has become an important chal...
Abstract—This paper seeks to combine linear time-invariant (LTI) filtering and sparsity-based denois...
One of the most promising alternative imaging modalities for breast cancer detection involved the us...
This chapter studies the problem of time-series classification and presents an overview of recent de...
In this work we analyze the problem of the ghosting artifacts coming out from non-uniformity correct...
The LMS-based adaptive non-uniformity correction (NUC) technique, known in the literature as Scribne...
Near-infrared spectroscopy (NIRS) is susceptible to signal artifacts caused by relative motion betwe...
This report presents an algorithm for removing artifacts from EEG signal, which is based on the meth...
Abstract. A novel reconstruction technique, called Wiener Filtered Recon-struction Technique (WIRT),...