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Large-scale neural recording with high spatio-temporal resolution is essential for understanding information processing in brain, yet current neural interfaces fall far short of comprehensively capturing brain activity due to extremely high…

The recent introduction of portable, low-field MRI (LF-MRI) into the clinical setting has the potential to transform neuroimaging. However, LF-MRI is limited by lower resolution and signal-to-noise ratio, leading to incomplete…

This paper presents a novel multimodal framework to distinguish between different symptom classes of subjects in the schizophrenia spectrum and healthy controls using audio, video, and text modalities. We implemented Convolution Neural…

Audio and Speech Processing · Electrical Eng. & Systems 2024-09-17 Gowtham Premananth , Yashish M. Siriwardena , Philip Resnik , Sonia Bansal , Deanna L. Kelly , Carol Espy-Wilson

We have fabricated arrays of High-T$_c$ Superconducting Quantum Interference Devices (SQUIDs) with randomly distributed loop sizes as sensitive antennas for Radio-Frequency (RF) waves. These sub-wavelength size devices known as…

Human brain activity is based on electrochemical processes, which can only be measured invasively. Therefore, quantities such as magnetic flux density (MEG) or electric potential differences (EEG) are measured non-invasively in medicine and…

Numerical Analysis · Mathematics 2022-07-27 Sarah Leweke , Olaf Hauk , Volker Michel

Current techniques of neuroimaging, including electrical devices, are either of low spatiotemporal resolution or invasive, impeding multiscale monitoring of brain activity at both single cell and network levels. Overcoming this issue is of…

Neurofeedback is a promising approach for non-invasive modulation of human brain activity with applications for treatment of mental disorders and enhancement of brain performance. Neurofeedback techniques are commonly based on either…

Medical Physics · Physics 2013-12-10 Vadim Zotev , Raquel Phillips , Han Yuan , Masaya Misaki , Jerzy Bodurka

Brain tumor segmentation requires accurate identification of hierarchical regions including whole tumor (WT), tumor core (TC), and enhancing tumor (ET) from multi-sequence magnetic resonance imaging (MRI) images. Due to tumor tissue…

Computer Vision and Pattern Recognition · Computer Science 2025-09-23 Mingda Zhang , Yuyang Zheng , Ruixiang Tang , Jingru Qiu , Haiyan Ding

Exploiting multiple modes in a quantum acoustic device could enable applications in quantum information in a hardware-efficient setup, including quantum simulation in a synthetic dimension and continuous-variable quantum computing with…

Modeling effective representations using multiple views that positively influence each other is challenging, and the existing methods perform poorly on Electroencephalogram (EEG) signals for sleep-staging tasks. In this paper, we propose a…

Superconducting QUantum Interference Device (SQUID) microscopy has excellent magnetic field sensitivity, but suffers from modest spatial resolution when compared with other scanning probes. This spatial resolution is determined by both the…

Magnetoencephalographic (MEG) measurements record magnetic fields generated from neurons while information is being processed in the brain. The inverse problem of identifying sources of biomagnetic fields and deducing their intensities from…

Neurons and Cognition · Quantitative Biology 2009-11-11 Hung-I Pai , Chih-Yuan Tseng , HC Lee

Magnetoencephalography (MEG) is an imaging technique used to measure the magnetic field outside the human head produced by the electrical activity inside the brain. The MEG inverse problem, identifying the location of the electrical sources…

Computation · Statistics 2014-08-01 Zhigang Yao , William F. Eddy

Ultra-high field MRI (7T+) unlocks a new era of brain research with superior resolution and signal-to-noise. Capturing intricate neural activity and detailed soft tissue pathology, this technology, coupled with advanced RF coil arrays,…

Medical Physics · Physics 2024-08-31 Debolina De , Aditya A. Bhosale , Xiaoliang Zhang

Classification of electroencephalogram (EEG) and electrocorticogram (ECoG) signals obtained during motor imagery (MI) has substantial application potential, including for communication assistance and rehabilitation support for patients with…

Computer Vision and Pattern Recognition · Computer Science 2025-10-20 Shuntaro Suzuki , Shunya Nagashima , Masayuki Hirata , Komei Sugiura

Intra-operative measurements of tissue shape and multi/ hyperspectral information have the potential to provide surgical guidance and decision making support. We report an optical probe based system to combine sparse hyperspectral…

Computer Vision and Pattern Recognition · Computer Science 2017-06-22 Jianyu Lin , Neil T. Clancy , Yang Hu , Ji Qi , Taran Tatla , Danail Stoyanov , Lena Maier-Hein , Daniel S. Elson

Recent developments in low-field (LF) magnetic resonance imaging (MRI) systems present remarkable opportunities for affordable and widespread MRI access. A robust denoising method to overcome the intrinsic low signal-noise-ratio (SNR)…

Image and Video Processing · Electrical Eng. & Systems 2024-05-01 Zheren Zhu , Azaan Rehman , Xiaozhi Cao , Congyu Liao , Yoo Jin Lee , Michael Ohliger , Hui Xue , Yang Yang

Ultrahigh field (UHF) Magnetic Resonance Imaging (MRI) offers an elevated signal-to-noise ratio (SNR), enabling exceptionally high spatial resolution that benefits both clinical diagnostics and advanced research. However, the jump to higher…

Computer Vision and Pattern Recognition · Computer Science 2025-11-26 Zhengyi Lu , Hao Liang , Ming Lu , Xiao Wang , Xinqiang Yan , Yuankai Huo

High-density electroencephalography (HD-EEG) enables fine-grained measurement of cortical activity but requires expensive hardware and lengthy setup times, limiting its clinical and research accessibility. We propose EMAG (EEG Mixture of…

Machine Learning · Computer Science 2026-05-29 Alex Lazarovich , Ofir Itzhak Shahar , Gur Elkin , Ohad Ben-Shahar

In this paper we propose a novel method for the segmentation of longitudinal brain MRI scans of patients suffering from Multiple Sclerosis. The method builds upon an existing cross-sectional method for simultaneous whole-brain and lesion…

Image and Video Processing · Electrical Eng. & Systems 2021-01-05 Stefano Cerri , Andrew Hoopes , Douglas N. Greve , Mark Mühlau , Koen Van Leemput
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