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Related papers: Deconvolution of the Functional Ultrasound Respons…

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Transient brain-wide neuroimaging on a microscopic scale is pivotal for brain research, yet current modalities face challenges in meeting such spatiotemporal requirements. Functional ultrasound (fUS) enables transient neurovascular imaging…

Medical Physics · Physics 2025-12-09 Yang Cai , Shaoyuan Yan , Long Xu , Yanfeng Zhu , Bo Li , Kailiang Xu

Ultrasound is widely used in medical diagnostics allowing for accessible and powerful imaging but suffers from resolution limitations due to diffraction and the finite aperture of the imaging system, which restricts diagnostic use. The…

Computer Vision and Pattern Recognition · Computer Science 2024-08-08 Felix Duelmer , Walter Simson , Mohammad Farid Azampour , Magdalena Wysocki , Angelos Karlas , Nassir Navab

The impulse response function (IRF) of a localized bolus in cerebral blood flow codes important information on the tissue type. It is indirectly accessible both from MR- and CT-imaging methods, at least in principle. In practice, however,…

Tissues and Organs · Quantitative Biology 2014-09-30 Evelyn Rost , Ralf Geske , Michael Baake

Objective: The brain operates via generation, transmission and integration of neuronal signals and most neurological disorders are related to perturbation of these processes. Neurostimulation by Focused Ultrasound (FUS) is a promising…

Functional ultrasound imaging (fUSI) is a cutting-edge technology that measures changes in cerebral blood volume (CBV) by detecting backscattered echoes from red blood cells moving within its field of view (FOV). It offers high…

Neurons and Cognition · Quantitative Biology 2025-08-20 Jared Deighton , Shan Zhong , Kofi Agyeman , Wooseong Choi , Charles Liu , Darrin Lee , Vasileios Maroulas , Vasileios Christopoulos

In the current paper, we introduce a parametric data-driven model for functional near-infrared spectroscopy that decomposes a signal into a series of independent, rescaled, time-shifted, hemodynamic basis functions. Each decomposed waveform…

Signal Processing · Electrical Eng. & Systems 2020-01-24 Marco A. Pinto-Orellana , Diego C. Nascimento , Peyman Mirtaheri , Rune Jonassen , Anis Yazidi , Hugo L. Hammer

Non-invasive methods to measure brain activity are important to understand cognitive processes in the human brain. A prominent example is functional magnetic resonance imaging (fMRI), which is a noisy measurement of a delayed signal that…

Neurons and Cognition · Quantitative Biology 2020-08-17 Hans-Christian Ruiz-Euler , Jose R. Ferreira Marques , Hilbert J. Kappen

Deconvolution of the hemodynamic response is an important step to access short timescales of brain activity recorded by functional magnetic resonance imaging (fMRI). Albeit conventional deconvolution algorithms have been around for a long…

Neurons and Cognition · Quantitative Biology 2023-10-19 Eneko Uruñuela , Thomas A. W. Bolton , Dimitri Van De Ville , César Caballero-Gaudes

Super-resolution ultrasound imaging through microbubble (MB) localisation and tracking, also known as ultrasound localisation microscopy, allows non-invasive sub-diffraction resolution imaging of microvasculature in animals and humans. The…

Image and Video Processing · Electrical Eng. & Systems 2025-05-23 Su Yan , Clotilde Vié , Marcelo Lerendegui , Herman Verinaz-Jadan , Jipeng Yan , Martina Tashkova , James Burn , Bingxue Wang , Gary Frost , Kevin G. Murphy , Meng-Xing Tang

We proposed a deconvolution optical-resolution photoacoustic microscope for high -resolution imaging of brain. The focal spot of the photoacoustic microscopy is measured to obtain the lateral PSF (point spread function) of the system.…

Medical Physics · Physics 2020-11-05 Xianlin Song , Lingfang Song , Anqing Chen , Jianshuang Wei

This thesis delves into the world of non-invasive electrophysiological brain signals like electroencephalography (EEG) and magnetoencephalography (MEG), focusing on modelling and decoding such data. The research aims to investigate what…

Signal Processing · Electrical Eng. & Systems 2025-10-30 Richard Csaky

We introduce a novel data-driven approach to discover and decode features in the neural code coming from large population neural recordings with minimal assumptions, using cohomological feature extraction. We apply our approach to neural…

Neurons and Cognition · Quantitative Biology 2018-09-11 Erik Rybakken , Nils Baas , Benjamin Dunn

Diffusion-weighted magnetic resonance imaging (DW-MRI) is a critical imaging method for capturing and modeling tissue microarchitecture at a millimeter scale. A common practice to model the measured DW-MRI signal is via fiber orientation…

Functional brain imaging through electroencephalography (EEG) relies upon the analysis and interpretation of high-dimensional, spatially organized time series. We propose to represent time-localized frequency domain characterizations of EEG…

Decoding visual experiences from brain activity is a significant challenge. Existing fMRI-to-video methods often focus on semantic content while overlooking spatial and motion information. However, these aspects are all essential and are…

Computer Vision and Pattern Recognition · Computer Science 2025-04-02 Chong Li , Jingyang Huo , Weikang Gong , Yanwei Fu , Xiangyang Xue , Jianfeng Feng

Segmentation of medical images is a fundamental task with numerous applications. While MRI, CT, and PET modalities have significantly benefited from deep learning segmentation techniques, more recent modalities, like functional ultrasound…

Image and Video Processing · Electrical Eng. & Systems 2025-07-24 Hana Sebia , Thomas Guyet , Mickaël Pereira , Marco Valdebenito , Hugues Berry , Benjamin Vidal

Decoding visual stimuli from neural responses recorded by functional Magnetic Resonance Imaging (fMRI) presents an intriguing intersection between cognitive neuroscience and machine learning, promising advancements in understanding human…

Computer Vision and Pattern Recognition · Computer Science 2023-12-29 Jingyuan Sun , Mingxiao Li , Zijiao Chen , Yunhao Zhang , Shaonan Wang , Marie-Francine Moens

Standard detection of evoked brain activity in functional MRI (fMRI) relies on a fixed and known shape of the impulse response of the neurovascular coupling, namely the hemodynamic response function (HRF). To cope with this issue, the joint…

Applications · Statistics 2015-01-07 Aina Frau-Pascual , Thomas Vincent , Florence Forbes , Philippe Ciuciu

Poor resolution of ultrasound images due to convolution of the tissue reflectivity function (TRF) with the system point spread function (PSF) is a major issue in medical ultrasound imaging. In this paper, we propose a correlation…

Signal Processing · Electrical Eng. & Systems 2018-06-08 Jayanta Dey , Md. Kamrul Hasan

It is important to properly correct for measurement error when estimating density functions associated with biomedical variables. These estimators that adjust for measurement error are broadly referred to as density deconvolution…

Methodology · Statistics 2018-06-06 Linh Nghiem , Cornelis J. Potgieter
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