Results 151 to 160 of about 1,285,227 (187)

Spatially Adaptive Kernels for Adaptive Spatial Filtering of fMRI Data

The 2006 IEEE International Joint Conference on Neural Network Proceedings, 2006
Making use of neighborhood time series is an effective way of noise reduction in fMRI data. However the conventional averaging methods blur activated areas. In this paper, a filter with adaptive kernel is designed such that its kernel size and direction are defined at each voxel.
V. Taimouri, G.-A. Hossein-Zadeh, H. Soltanian-Zadeh   +2 more
openaire   +1 more source

Group-level adaptive-analysis of task fMRI data

ISMRM Annual Meeting, 2023
A task-fMRI group-level analysis method is proposed to incorporate spatial covariance structures in fMRI data using the subject-level steerable filter smoothing with various full-wide-half-maximums followed by a group-level one-step optimization. Subject-level smoothed time series are further orthogonalized to guarantee non-overlapped contributions to ...
Xiaowei Zhuang, Zhengshi Yang, Tim Curran, Rajesh Nandy, Mark Lowe, Dietmar Cordes   +5 more
openaire   +1 more source

Rotational Invariance in Adaptive fMRI Data Analysis

2006 International Conference on Image Processing, 2006
It has previously been shown that canonical correlation analysis (CCA) works well for detecting neural activity in fMRI data. This is due to the ability of CCA to perform simultaneous temporal modeling and adaptive spatial filtering of the data. In this paper, we demonstrate that our previously proposed method for CCA-based fMRI data analysis does not ...
Joakim Rydell, Hans Knutsson, Magnus Borga   +2 more
openaire   +1 more source

Prompt Your Brain: Scaffold Prompt Tuning for Efficient Adaptation of fMRI Pre-trained Model

International Conference on Medical Image Computing and Computer-Assisted Intervention
We introduce Scaffold Prompt Tuning (ScaPT), a novel prompt-based framework for adapting large-scale functional magnetic resonance imaging (fMRI) pre-trained models to downstream tasks, with high parameter efficiency and improved performance compared to ...
Zijian Dong, Yilei Wu, Zijiao Chen, Yichi Zhang, Yueming Jin, Juan Helen Zhou   +5 more
semanticscholar   +1 more source

An Adaptive Regression Mixture Model for fMRI Cluster Analysis

IEEE Transactions on Medical Imaging, 2013
Functional magnetic resonance imaging (fMRI) has become one of the most important techniques for studying the human brain in action. A common problem in fMRI analysis is the detection of activated brain regions in response to an experimental task. In this work we propose a novel clustering approach for addressing this issue using an adaptive regression
Vangelis P, Oikonomou, Konstantinos, Blekas   +1 more
openaire   +2 more sources

Decoding Brain States From fMRI Signals by Using Unsupervised Domain Adaptation

IEEE journal of biomedical and health informatics, 2020
With the development of deep learning in medical image analysis, decoding brain states from functional magnetic resonance imaging (fMRI) signals has made significant progress. Previous studies often utilized deep neural networks to automatically classify
Yufei Gao, Yameng Zhang, Zhiyuan Cao, Xiaojuan Guo, Jia-cai Zhang   +4 more
semanticscholar   +1 more source

Data from: Color contrast adaptation: fMRI fails to predict behavioral adaptation

2019
Work published as: Goddard E, Chang DHF, Hess RF, Mullen KT (2019) Color contrast adaptation: fMRI fails to predict behavioral adaptation. Neuroimage (accepted July 2019). DOI: https://doi.org/10.1016/j.neuroimage.2019.116032. Please cite this paper if you use the data on this project.
Goddard, Erin, Mullen, Kathy
openaire   +1 more source

Smoothing FMRI Data Using an Adaptive Wiener Filter

2015
The analysis of fMRI allows mapping the brain and identifying brain regions activated by a particular task. Prior to the analysis, several steps are carried out to prepare the data. One of these is the spatial smoothing whose aim is to eliminate the noise which can cause errors in the analysis.
Bartés i Serrallonga, Manel, Serra Grabulosa, Josep M., Adan, Ana, Falcón, Carles, Bargalló, Núria, Solé-Casals, Jordi   +5 more
openaire   +1 more source

Integrative oncology: Addressing the global challenges of cancer prevention and treatment

Ca-A Cancer Journal for Clinicians, 2022
Jun J Mao,, Msce, Lorenzo Cohen, Karen M Mustian   +2 more
exaly  

Spatiotopic updating across saccades revealed by spatially‐specific fMRI adaptation

NeuroImage, 2017
S. Fairhall, J. Schwarzbach, A. Lingnau, M. V. Koningsbruggen, D. Melcher   +4 more
semanticscholar   +1 more source