Due to its low intensity, measurement of transient-evoked otoacoustic emission (TEOAE) requires repeated stimulation. When any acoustic artifact occurs, an entire click interval is typically abandoned. Here, a point-wise artifact rejection strategy is proposed, and it partially preserves the data when artifacts occur in an interval. At the noisiest setting (-46 dB signal-to-noise ratio) the proposed strategy retains four times more data and thereby reduces the root mean square signal estimation error by over 60%. Consequently, the group delay can be calculated more accurately. These findings might facilitate TEOAE measurement at home or in other noisy environments in the future.
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http://dx.doi.org/10.1121/10.0009393 | DOI Listing |
Magn Reson Med
March 2025
MRILab, Institute for Molecular Imaging and Instrumentation (i3M), Spanish National Research Council (CSIC), Universitat Politècnica de València (UPV), Valencia, Spain.
Purpose: Zero-echo-time (ZTE) sequences have proven a powerful tool for MRI of ultrashort tissues, but they fail to produce useful images in the presence of strong field inhomogeneities (14 000 ppm). Here we seek a method to correct reconstruction artifacts from non-Cartesian acquisitions in highly inhomogeneous , where the standard double-shot gradient-echo approach to field mapping fails.
Methods: We present a technique based on magnetic field maps obtained from two geometric distortion-free point-wise (SPRITE) acquisitions.
IEEE J Biomed Health Inform
April 2024
Electrocardiogram (ECG) signals frequently encounter diverse types of noise, such as baseline wander (BW), electrode motion (EM) artifacts, muscle artifact (MA), and others. These noises often occur in combination during the actual data acquisition process, resulting in erroneous or perplexing interpretations for cardiologists. To suppress random mixed noise (RMN) in ECG with less distortion, we propose a Transformer-based Convolutional Denoising AutoEncoder model (TCDAE) in this study.
View Article and Find Full Text PDFbioRxiv
September 2023
Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins School of Medicine.
Neural networks are potentially valuable for many of the challenges associated with MRS data. The purpose of this manuscript is to describe the AGNOSTIC dataset, which contains 259,200 synthetic H MRS examples for training and testing neural networks. AGNOSTIC was created using 270 basis sets that were simulated across 18 field strengths and 15 echo times.
View Article and Find Full Text PDFComput Biol Med
January 2023
Department of Computer Science and Engineering, UNIST, Ulsan, South Korea. Electronic address:
Background: Anterior temporal lobe resection is an effective treatment for temporal lobe epilepsy. The post-surgical structural changes could influence the follow-up treatment. Capturing post-surgical changes necessitates a well-established cortical shape correspondence between pre- and post-surgical surfaces.
View Article and Find Full Text PDFJASA Express Lett
February 2022
Department of Electrical Engineering, National Tsing Hua University, Hsinchu, 300044, Taiwan
Due to its low intensity, measurement of transient-evoked otoacoustic emission (TEOAE) requires repeated stimulation. When any acoustic artifact occurs, an entire click interval is typically abandoned. Here, a point-wise artifact rejection strategy is proposed, and it partially preserves the data when artifacts occur in an interval.
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