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Low-Rank and Framelet Based Sparsity Decomposition for Interventional MRI Reconstruction [article]

Zhao He, Ya-Nan Zhu, Suhao Qiu, Xiaoqun Zhang, Yuan Feng
2021 arXiv   pre-print
Methods: We proposed a low-rank and sparsity (LS) decomposition algorithm with framelet transform to reconstruct the interventional feature with a high temporal resolution.  ...  Different from the existing LS based algorithm, we utilized the spatial sparsity of both the low-rank and sparsity components.  ...  In this study, we proposed a low-rank and sparsity decomposition (LS) with framelet transform (LSF) for reconstruction.  ... 
arXiv:2107.11947v1 fatcat:qwxzaltg5rd6vjvjrulxr7adrm

Image Reconstruction: From Sparsity to Data-adaptive Methods and Machine Learning [article]

Saiprasad Ravishankar, Jong Chul Ye, Jeffrey A. Fessler
2019 arXiv   pre-print
This paper focuses on the two most recent trends in medical image reconstruction: methods based on sparsity or low-rank models, and data-driven methods based on machine learning techniques.  ...  These methods typically involve mathematical image models involving assumptions such as sparsity or low-rank.  ...  Sections III and IV describe sparsity and low-rank based approaches for image reconstruction.  ... 
arXiv:1904.02816v2 fatcat:ehahzrib2ff3dl5yl6pa7xpf24

Front Matter: Volume 9412

Proceedings of SPIE, Christoph Hoeschen, Despina Kontos, Thomas G. Flohr
2015 Medical Imaging 2015: Physics of Medical Imaging  
-8] 9412 0A Clinical image benefits after model-based reconstruction for low dose dedicated breast tomosynthesis [9412-9] 9412 0B Rank-sparsity constrained spectro-temporal reconstruction for retrospectively  ...  gated dynamic CT [9412-10] SESSION 3 DETECTOR TECHNOLOGY 0C Low-dose performance of wafer-scale CMOS-based x-ray detectors 9412 0D Apodized-aperture pixel design to increase high-frequency DQE and reduce  ...  and self-healing silicone as phantom materials [9412-126] 9412 3H SPECT reconstruction using DCT-induced tight framelet regularization [9412-127] 9412 3I Robust iterative image reconstruction for  ... 
doi:10.1117/12.2184295 fatcat:ewelisqkxvbwbnxeiwhldcrfpi

A Long Short-term Memory Based Recurrent Neural Network for Interventional MRI Reconstruction [article]

Ruiyang Zhao, Zhao He, Tao Wang, Suhao Qiu, Pawel Herman, Yanle Hu, Chencheng Zhang, Dinggang Shen, Bomin Sun, Guang-Zhong Yang, Yuan Feng
2022 arXiv   pre-print
Different from retrospective reconstruction in conventional dynamic imaging, i-MRI for DBS has to acquire and reconstruct the interventional images sequentially online.  ...  The proposed algorithm has the potential to achieve real-time i-MRI for DBS and can be used for general purpose MR-guided intervention.  ...  Zhi-Pei Liang, Jun Zhao, and Yiping Du for their helpful discussions.  ... 
arXiv:2203.14769v2 fatcat:dvhtntb43vgj7norjy7wugcf6a

Wavelet-Based Representation of Biological Shapes [chapter]

Bin Dong, Yu Mao, Ivo D. Dinov, Zhuowen Tu, Yonggang Shi, Yalin Wang, Arthur W. Toga
2009 Lecture Notes in Computer Science  
We apply the new technique to multi-spectral shape decomposition and study shape variability between populations using brain cortical and subcortical surfaces.  ...  Our results are very promising and, comparing to the spherical-wavelets method, our approach is more compact and allows utilization of diverse wavelet bases.  ...  Information on the National Centers for Biomedical Computing can be obtained from http://nihroadmap.nih.gov/bioinformatics.  ... 
doi:10.1007/978-3-642-10331-5_89 fatcat:olk6tgxvirbklhijwndkixjr44

Towards Omni-Tomography—Grand Fusion of Multiple Modalities for Simultaneous Interior Tomography

Ge Wang, Jie Zhang, Hao Gao, Victor Weir, Hengyong Yu, Wenxiang Cong, Xiaochen Xu, Haiou Shen, James Bennett, Mark Furth, Yue Wang, Michael Vannier (+1 others)
2012 PLoS ONE  
Over the past decade, two approaches have been used for multimodality fusion: Software based image registration and hybrid scanners such as PET-CT, PET-MRI, and SPECT-CT among others.  ...  We recently elevated interior tomography from its origin in computed tomography (CT) to a general tomographic principle, and proved its validity for other tomographic modalities including SPECT, MRI, and  ...  Tiange Zhuang, Jun Zhao, Yang Lv, Erik Ritman, Erwei Bai, Robert Kraft, Craig Hamilton, Youngkyoo Jung, Wenbing Yun, Yantian Zhang, Alexander Katsevich, and others for helpful discussions.  ... 
doi:10.1371/journal.pone.0039700 pmid:22768108 pmcid:PMC3387257 fatcat:y3rybizkhjf4lkhxim6bycuiia

MRI Reconstruction Using Markov Random Field and Total Variation as Composite Prior

Marko Panić, Dušan Jakovetić, Dejan Vukobratović, Vladimir Crnojević, Aleksandra Pižurica
2020 Sensors  
In this paper, we develop a novel reconstruction method, which includes a composite prior based on an MRF model and Total Variation (TV).  ...  We use an anisotropic MRF model and propose an original data-driven method for the adaptive estimation of its parameters.  ...  P-LORAKS: Low-rank modeling of local k-space neighborhoods with parallel imaging data. Magn. Reson. Med.2016, 75, 1499–1514.  ... 
doi:10.3390/s20113185 pmid:32503338 pmcid:PMC7309077 fatcat:aqzjjypw25ahpcs6vdahfa33oe

The Modern Mathematics of Deep Learning [article]

Julius Berner, Philipp Grohs, Gitta Kutyniok, Philipp Petersen
2021 arXiv   pre-print
For selected approaches, we describe the main ideas in more detail.  ...  surprisingly successful optimization performance despite the non-convexity of the problem, understanding what features are learned, why deep architectures perform exceptionally well in physical problems, and  ...  Standard numerical approaches (notably the Multireference Hartree Fock Method, see [SO12]) use a low rank approach to minimize Qn (8.3).  ... 
arXiv:2105.04026v1 fatcat:lxnfyzr6qfasneo433inpgseia

Smart Nanoscopy: A Review of Computational Approaches to achieve Super-resolved Optical Microscopy

Shiraz S. Kaderuppan, Wai Leong Eugene Wong, Anurag Sharma, Wai Lok Woo
2020 IEEE Access  
in computing hardware, such as multi-core CPUs & GPUs, low-latency RAM and hard-drive capacities.  ...  through the development of techniques such as stimulated emission and depletion (STED) microscopy, photoactivated localization microscopy (PALM) and stochastic optical reconstruction microscopy (STORM  ...  reconstruction [139] .  ... 
doi:10.1109/access.2020.3040319 fatcat:sw3zqkv6zrcajdlydpyqnjgj34

Advances in Electron Microscopy with Deep Learning

Jeffrey Ede
2020 Zenodo  
generative adversarial networks for exit wavefunction reconstruction from single transmission electron micrographs.  ...  Philosophy in Physics is typeset for physical printing and binding.  ...  Acknowledgements Thanks go to Jeremy Sloan and Martin Lotz for internally reviewing this article.  ... 
doi:10.5281/zenodo.4591029 fatcat:zn2hvfyupvdwlnvsscdgswayci

Advances in Electron Microscopy with Deep Learning

Jeffrey Ede
2020 Zenodo  
generative adversarial networks for exit wavefunction reconstruction from single transmission electron micrographs.  ...  Philosophy in Physics is typeset for physical printing and binding.  ...  Acknowledgements Thanks go to Jeremy Sloan and Martin Lotz for internally reviewing this article.  ... 
doi:10.5281/zenodo.4598227 fatcat:hm2ksetmsvf37adjjefmmbakvq

Advances in Electron Microscopy with Deep Learning

Jeffrey Ede
2020 Zenodo  
generative adversarial networks for exit wavefunction reconstruction from single transmission electron micrographs.  ...  in Physics will be typeset for physical printing and binding.  ...  Acknowledgements Thanks go to Jeremy Sloan and Martin Lotz for internally reviewing this article.  ... 
doi:10.5281/zenodo.4399748 fatcat:63ggmnviczg6vlnqugbnrexsgy

Advances in Electron Microscopy with Deep Learning

Jeffrey Ede
2020 Zenodo  
generative adversarial networks for exit wavefunction reconstruction from single transmission electron micrographs.  ...  in Physics will be typeset for physical printing and binding.  ...  Acknowledgements Thanks go to Jeremy Sloan and Martin Lotz for internally reviewing this article.  ... 
doi:10.5281/zenodo.4429792 fatcat:qs6yuapx4vdbdmwna7ix7nnwty

Advances in Electron Microscopy with Deep Learning

Jeffrey Ede
2020 Zenodo  
generative adversarial networks for exit wavefunction reconstruction from single transmission electron micrographs.  ...  in Physics will be typeset for physical printing and binding.  ...  Acknowledgements Thanks go to Jeremy Sloan and Martin Lotz for internally reviewing this article.  ... 
doi:10.5281/zenodo.4413249 fatcat:35qbhenysfhvza2roihx52afuy

Advances in Electron Microscopy with Deep Learning

Jeffrey Ede
2020 Zenodo  
generative adversarial networks for exit wavefunction reconstruction from single transmission electron micrographs.  ...  in Physics will be typeset for physical printing and binding.  ...  Acknowledgements Thanks go to Jeremy Sloan and Martin Lotz for internally reviewing this article.  ... 
doi:10.5281/zenodo.4415407 fatcat:6dejwzzpmfegnfuktrld6zgpiq