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Temporal Feature Fusion with Sampling Pattern Optimization for Multi-echo Gradient Echo Acquisition and Image Reconstruction [article]

Jinwei Zhang, Hang Zhang, Chao Li, Pascal Spincemaille, Mert Sabuncu, Thanh D. Nguyen, Yi Wang
2021 arXiv   pre-print
In this work, we focus on optimizing the acquisition and reconstruction process of multi-echo gradient echo pulse sequence for quantitative susceptibility mapping as one important quantitative imaging  ...  A multi-echo sampling pattern optimization block extended from LOUPE-ST is proposed to optimize the k-space sampling patterns along echoes.  ...  We extend LOUPE-ST [27] to the multi-echo scenario for temporal sampling pattern optimization and propose a novel temporal feature fusion block into a deep ADMM based unrolled reconstruction network  ... 
arXiv:2103.05878v1 fatcat:paisyy3tzvhwrpibrocpfl34fq

Investigation of in Vivo Human Cardiac Diffusion Tensor Imaging Using Unsupervised Dense Encoder-Fusion-Decoder Network

Zeyu DENG, Lihui Wang, Qiang Wu, Qijian Chen, Ying Cao, Li WANG, Xinyu Cheng, Jian ZHANG, Yuemin Zhu
2020 IEEE Access  
The denseencoder and decoder are trained firstly with DW images acquired at different trigger delays in an unsupervised manner for extracting local and global features.  ...  A fusion strategy is then designed to fuse the extracted features. Finally, the well-trained decoder is used to reconstruct the fused DW image from the fused features.  ...  By shifting the TDs with an interval of 10 ms for 9 times, 130 multi-phase images (10 time points × 13 images) are obtained for each slice.  ... 
doi:10.1109/access.2020.3040330 fatcat:szbzk46z7jc3rccudlygpohfea

Advances in diffusion MRI acquisition and processing in the Human Connectome Project

Stamatios N. Sotiropoulos, Saad Jbabdi, Junqian Xu, Jesper L. Andersson, Steen Moeller, Edward J. Auerbach, Matthew F. Glasser, Moises Hernandez, Guillermo Sapiro, Mark Jenkinson, David A. Feinberg, Essa Yacoub (+4 others)
2013 NeuroImage  
A consortium of HCP investigators will study a population of 1200 healthy adults using multiple imaging modalities, along with extensive behavioral and genetic data.  ...  These advances result from 2 years of intensive efforts in optimising many aspects of data acquisition and processing during the piloting phase of the project.  ...  Acknowledgments We acknowledge support from the Human Connectome Project (1U54MH091657-01), from the 16 NIH Institutes and Centers that support the NIH Blueprint for Neuroscience Research, plus grants  ... 
doi:10.1016/j.neuroimage.2013.05.057 pmid:23702418 pmcid:PMC3720790 fatcat:3e3hkqbzdjcmtnx4anwqp3swvi

CNN-Based Invertible Wavelet Scattering for the Investigation of Diffusion Properties of the In Vivo Human Heart in Diffusion Tensor Imaging [article]

Zeyu Deng, Lihui Wang, Zixiang Kuai, Qijian Chen, Xinyu Cheng, Feng Yang, Jie Yang, Yuemin Zhu
2019 arXiv   pre-print
We propose a novel motion-compensation method for investigating in vivo myocardium structures in DTI with free-breathing acquisitions.  ...  The results on both simulated and acquired in vivo cardiac DW images showed that the proposed WSCNN method effectively compensates for motion-induced signal loss and produces in vivo cardiac DW images  ...  To reduce the impact of eddy current artifacts, a single-shot twice-refocused spin-echo echo-planar imaging (EPI) sequence with optimized bipolar diffusion encoding gradients was used.  ... 
arXiv:1912.07776v1 fatcat:j7i7yl65dfbjvdswfdwyvexwli

Multi-parametric neuroimaging reproducibility: A 3-T resource study

Bennett A. Landman, Alan J. Huang, Aliya Gifford, Deepti S. Vikram, Issel Anne L. Lim, Jonathan A.D. Farrell, John A. Bogovic, Jun Hua, Min Chen, Samson Jarso, Seth A. Smith, Suresh Joel (+5 others)
2011 NeuroImage  
Additionally, it establishes a baseline for continuing development and optimization of multi-parametric imaging protocols.  ...  These analyses typically exploit carefully optimized protocols for specific imaging targets.  ...  Peter C.M. van Zijl is a paid lecturer for Philips Healthcare and has technology licensed to them.  ... 
doi:10.1016/j.neuroimage.2010.11.047 pmid:21094686 pmcid:PMC3020263 fatcat:t7k6n2dlfvcmhgs56vwed5ao6y

Multi-Site Diagnostic Classification of Schizophrenia Using Discriminant Deep Learning with Functional Connectivity MRI

Ling-Li Zeng, Huaning Wang, Panpan Hu, Bo Yang, Weidan Pu, Hui Shen, Xingui Chen, Zhening Liu, Hong Yin, Qingrong Tan, Kai Wang, Dewen Hu
2018 EBioMedicine  
Methods: A large multi-site functional MRI sample (n = 734, including 357 schizophrenic patients from seven imaging resources) was collected, and a deep discriminant autoencoder network, aimed at learning  ...  Advanced deep learning methods may be capable of learning subtle hidden patterns from high dimensional imaging data, overcome potential site-related variation, and achieve reproducible cross-site classification  ...  Acknowledgments This work was supported by the National Science Foundation of China (61722313, 61503397, 61420106001, 61773391, and 81571309), the Fok Ying Tung Education Foundation (161057)  ... 
doi:10.1016/j.ebiom.2018.03.017 pmid:29622496 pmcid:PMC5952341 fatcat:op763xk53jghxk2hreux255gmu

Motion Compensated Magnetic Resonance Reconstruction Using Inverse-Consistent Deformable Registration: Application to Real-Time Cine Imaging [chapter]

Hui Xue, Yu Ding, Christoph Guetter, Marie-Pierre Jolly, Jens Guehring, Sven Zuehlsdorff, Orlando P. Simonetti
2011 Lecture Notes in Computer Science  
Recent theoretical advances incorporate explicit rigid and non-rigid motion compensation into conventional image reconstruction for multi-shot acquisitions and recover motion-free images by solving a general  ...  We further extend this framework for multi-coil motion compensated image reconstruction using the eigen-mode analysis.  ...  Authors would like to thank Dr Philip Batchlor (King's College London) for discussion and providing general matrix inversion program.  ... 
doi:10.1007/978-3-642-23623-5_71 fatcat:s2ygnsrdvzfgfp5faympruwh5y

2020 Index IEEE Transactions on Signal Processing Vol. 68

2020 IEEE Transactions on Signal Processing  
., and Rahmani, M., One-Step Prediction for Discrete Time-Varying Nonlinear Systems With Unknown Inputs and Correlated Noises; TSP  ...  ., +, TSP 2020 747-763 Sampling and Reconstruction of Bandlimited Signals With Multi-Channel Time Encoding.  ...  ., +, TSP 2020 2770-2783 Sampling and Reconstruction of Bandlimited Signals With Multi-Channel Time Encoding.  ... 
doi:10.1109/tsp.2021.3055469 fatcat:6uswtuxm5ba6zahdwh5atxhcsy

Magnetic Resonance Imaging of Structure and Coarsening in Three-Dimensional Foams

Burkhard A. Prause, James A. Glazier
2001 Proceedings of the 5th Experimental Chaos Conference  
We have developed an MRI technique to optimize the image quality for foams with very low liquid fraction.  ...  Volumetric imaging of coarsening foams required a robust imaging method with sufficient spatial and temporal resolution to resolve the small liquid accumulations in the foam's Plateau borders.  ...  Our efforts during the visits concentrated on the possibility of using gradient echo techniques for rapid multi-slice image acquisitions.  ... 
doi:10.1142/9789812811516_0041 fatcat:vuwsnhqpyba5lltonmejmmape4

Two-Stream Deep Fusion Network Based on VAE and CNN for Synthetic Aperture Radar Target Recognition

Lan Du, Lu Li, Yuchen Guo, Yan Wang, Ke Ren, Jian Chen
2021 Remote Sensing  
Following the feature extraction stage, a fusion module is utilized to integrate the latent probabilistic distribution characteristic and the structure characteristic for the reflecting target information  ...  Therefore, in this paper, we propose a novel end-to-end two stream fusion network to make full use of the different characteristics obtained from modeling HRRP data and SAR images, respectively, for SAR  ...  Several works focusing on image segmentation also use feature level fusion to fuse multi-level features [45] [46] [47] .  ... 
doi:10.3390/rs13204021 fatcat:lbla7u2dojgqpl7xa7ot6je44i

Enhanced disease characterization through multi network functional normalization in fMRI

Mustafa S. Çetin, Siddharth Khullar, Eswar Damaraju, Andrew M. Michael, Stefi A. Baum, Vince D. Calhoun
2015 Frontiers in Neuroscience  
for multi groups of subjects.  ...  Also, these networks exhibit temporal and spatial modulation during cognitive task vs. rest which shows the existence of common spatial excitation patterns between these identified networks.  ...  Following parameters were set for acquiring the functional scans trans-axially with gradient-echo EPI: repeat time (TR) = 1.50 s, echo time (TE) = 27 ms, field of view = 24 cm, acquisition matrix = 64  ... 
doi:10.3389/fnins.2015.00095 pmid:25873853 pmcid:PMC4379901 fatcat:xiuswqscrfbxnnjbeleppalf5u

Curvelet Transform-based volume fusion for correcting signal loss artifacts in Time-of-Flight Magnetic Resonance Angiography data

Ahmadreza Baghaie, Susanne Schnell, Ali Bakhshinejad, Mojtaba F. Fathi, Roshan M. D'Souza, Vitaliy L. Rayz
2018 Computers in Biology and Medicine  
Experiments show the superiority of the proposed approach in comparison to other multi-resolution 3D Wavelet-based image fusion methodologies.  ...  In this work a 3D Curvelet Transform-based image fusion approach is proposed for signal loss artifact reduction of TOF volume data.  ...  However, DT-DWT and DT-CWT suffer from blurred edges and features, especially in regions with small features, as is obvious from the difference maps with the ground truth.  ... 
doi:10.1016/j.compbiomed.2018.06.008 pmid:29929053 pmcid:PMC6077095 fatcat:clr567uwjzff3bn36hltefsdmm

Pattern identification of biomedical images with time series: Contrasting THz pulse imaging with DCE-MRIs

Xiao-Xia Yin, Sillas Hadjiloucas, Yanchun Zhang, Min-Ying Su, Yuan Miao, Derek Abbott
2016 Artificial Intelligence in Medicine  
The approach is also of interest for other emergent multi-channel biomedical imaging modalities and of relevance across the biomedical signal processing community. .au (X.-X.  ...  Yin). follows: Section 1 provides an introduction to THz-transient spectrometry as this is the more well-established modality for building THz imaging systems, together with an account of recent advances  ...  shows spatial and temporal information fusion with decreased number of dimensions for reduced computation cost.  ... 
doi:10.1016/j.artmed.2016.01.005 pmid:26951630 fatcat:usz7o4ejqbhbxntbu34zhg32iu

Role of Multiparametric MR Imaging in Malignancies of the Urogenital Tract

Alberto Diaz de Leon, Daniel Costa, Ivan Pedrosa
2016 Magnetic Resonance Imaging Clinics of North America  
Recently developed 3-D dual-echo Dixon-based acquisitions allow for acquisition of thinner, contiguous slices in a single breath-hold that can then be reconstructed into water, fat, IP, and OP imaging  ...  and opposed-phase (OP) images, or chemical shift imaging, of the abdomen are used in the renal mass and MRU protocols for the detection of intravoxel lipids.  ...  time-point approach for data analysis. 42 Diffusion-Weighted Imaging The technical parameters for DWI, including method of acquisition (FSE, gradient-echo, line scan, echo-planar imaging [EPI] , and  ... 
doi:10.1016/j.mric.2015.08.009 pmid:26613881 pmcid:PMC6247808 fatcat:ah7ksntftrf5zkljyesajdhsga

The cortical wiring scheme of hierarchical information processing [article]

Casey Paquola, Jakob Seidlitz, Oualid Benkarim, Jessica Royer, Petr Klimes, Richard A.I. Bethlehem, Sara Lariviere, Reinder Vos de Wael, Jeffrey Hall, Birgit Frauscher, Jonathan Smallwood, Boris Bernhardt
2020 bioRxiv   pre-print
Principal dimensions of this manifold recapitulated established sensory-limbic and anterior-posterior gradients of brain organisation, and were found to reflect neural and glial gradients of cytoarchitectural  ...  These results advance our understanding of how cell-specific neurobiological gradients produce a hierarchical cortical wiring scheme that is concordant with increasing functional sophistication of human  ...  Matthias Kirschner for his helpful insight on the manuscript, and the MRI and EEG technicians at the Montreal Neurological Institute.  ... 
doi:10.1101/2020.01.08.899583 fatcat:ytkw3asdcbhu7c2o5jyxfy67t4
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