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Detail-Preserving PET Reconstruction with Sparse Image Representation and Anatomical Priors [chapter]

Jieqing Jiao, Pawel Markiewicz, Ninon Burgos, David Atkinson, Brian Hutton, Simon Arridge, Sebastien Ourselin
2015 Lecture Notes in Computer Science  
Instead of a regular voxel grid, the sparse image representation jointly determined by the prior image and the PET data is used in reconstruction to leverage between the image details and smoothness, and  ...  and selectively smooth the image on a voxel basis in PET reconstruction.  ...  The sparse image representation is jointly derived from the anatomical prior image and the PET data, preserving the edges and anatomical details without degradation of the structures only present in the  ... 
doi:10.1007/978-3-319-19992-4_42 fatcat:z33o7afxfrdqbk22w74erk3qzq

PET Image Reconstruction Using Kernel Method

Guobao Wang, Jinyi Qi
2015 IEEE Transactions on Medical Imaging  
method with and without post-reconstruction denoising.  ...  Image reconstruction from low-count PET projection data is challenging because the inverse problem is ill-posed. Prior information can be used to improve image quality.  ...  Jian Zhou for generating the forward and back projectors for the 3D patient data, and Li Yang for the assistance in the processing of the patient data.  ... 
doi:10.1109/tmi.2014.2343916 pmid:25095249 pmcid:PMC4280333 fatcat:huex2re2cfcexhmcc3sltcohoe

Patch-based image reconstruction for PET using prior-image derived dictionaries

Marzieh S Tahaei, Andrew J Reader
2016 Physics in Medicine and Biology  
In PET image reconstruction, regularization is often needed to reduce the noise in the resulting images.  ...  This novel method is then utilized to find sparse coefficients for the patch-based basis vectors extracted from the MR image.  ...  According to EPSRC's policy framework on research data, figures and the reconstructed images of simulation and real data supporting this study are openly available at  ... 
doi:10.1088/0031-9155/61/18/6833 pmid:27581747 fatcat:esh7mfx2hrbkfhoxhxah23qyky

Coupled Feature Learning for Multimodal Medical Image Fusion [article]

Farshad G. Veshki, Nora Ouzir, Sergiy A. Vorobyov, Esa Ollila
2021 arXiv   pre-print
Specifically, the images to be fused are decomposed into coupled and independent components estimated using sparse representations with identical supports and a Pearson correlation constraint, respectively  ...  Experiments are conducted using various pairs of multimodal inputs, including real MR-CT and MR-PET images.  ...  For example, the images are separated into base and detail components prior to the dictionary learning phase in [11] .  ... 
arXiv:2102.08641v1 fatcat:62joyvffrzco3kyqozgqpb2xua

A Geometry-Informed Deep Learning Framework for Ultra-Sparse 3D Tomographic Image Reconstruction [article]

Liyue Shen, Wei Zhao, Dante Capaldi, John Pauly, Lei Xing
2021 arXiv   pre-print
We demonstrate that the seamless inclusion of known priors is essential to enhance the performance of 3D volumetric computed tomography imaging with ultra-sparse sampling.  ...  Here we establish a geometry-informed deep learning framework for ultra-sparse 3D tomographic image reconstruction.  ...  ACKNOWLEDGMENT The authors acknowledge the National Cancer Institute and the Foundation for the National Institutes of Health, and their critical role in the creation of the free publicly available LIDC  ... 
arXiv:2105.11692v1 fatcat:llurdy3edvcb5ajpfqpxupnbfi

Computer Vision in Healthcare Applications

Junfeng Gao, Yong Yang, Pan Lin, Dong Sun Park
2018 Journal of Healthcare Engineering  
The guest editors are very thankful to all the anonymous reviewers of the journal and the perseverant and generous support of the editor in chief. Junfeng Gao Yong Yang Pan Lin Dong Sun Park  ...  Acknowledgments This work was supported by the National Nature Science Foundation of China (61773408, 81271659, 61662026, and 61473221).  ...  Currently, many methods have been proposed to remove the noise and preserve the image details at the same time. M. Szczepański and K.  ... 
doi:10.1155/2018/5157020 pmid:29686826 pmcid:PMC5857319 fatcat:nouvaymmrbgircnal6irb2nynq

mage reconstruction for positron emission tomography based on patch‐based regularization and dictionary learning

Wanhong Zhang, Juan Gao, Yongfeng Yang, Dong Liang, Xin Liu, Hairong Zheng, Zhanli Hu
2019 Medical Physics (Lancaster)  
in reconstructed images.  ...  The results show that the proposed algorithm has the potential to improve the quality of PET image reconstruction.  ...  ACKNOWLEDGMENTS The authors thank the editor and anonymous reviewers for their constructive comments and suggestions. This work was Author to whom any correspondence should be addressed.  ... 
doi:10.1002/mp.13804 pmid:31494950 pmcid:PMC6899708 fatcat:s6sfcwcf2ne3znqt27omvzbcau

Incorporation of anatomical MRI knowledge for enhanced mapping of brain metabolism using functional PET

Viswanath P. Sudarshan, Shenpeng Li, Sharna D. Jamadar, Gary F. Egan, Suyash P. Awate, Zhaolin Chen
2021 NeuroImage  
In this work, a post-processing framework based on a magnetic resonance (MR) Bowsher-like prior was used to improve the spatial and temporal signal to noise characteristics of the fPET images.  ...  The framework extends the use of functional PET to investigate the dynamics of brain metabolic responses for faster presentation of brain activation tasks, and for applications in low dose PET imaging.  ...  We acknowledge the provision of Siemens e7tools used for reconstruction of the PET images.  ... 
doi:10.1016/j.neuroimage.2021.117928 pmid:33716154 fatcat:ewsf74rj4zb45ge35wbbed3hmi

Application of Image Fusion in Diagnosis and Treatment of Liver Cancer

Li, Zhu
2020 Applied Sciences  
With the accelerated development of medical imaging equipment and techniques, image fusion technology has been effectively applied for diagnosis, biopsy and radiofrequency ablation, especially for liver  ...  Using the image fusion technology, one could obtain real-time anatomical imaging superimposed by functional images showing the same plane to facilitate the diagnosis and treatments of liver tumors.  ...  sparse representation with multi-selection strategy and convolutional sparse representation.  ... 
doi:10.3390/app10031171 fatcat:yjvhqxhpevauxezinw5tjqsriu

Magnetic Resonance-Guided Positron Emission Tomography Image Reconstruction

Bing Bai, Quanzheng Li, Richard M. Leahy
2013 Seminars in nuclear medicine  
With the recent development of combined MR-PET scanners, it is possible to collect intrinsically coregistered MR images.  ...  It is therefore now possible to routinely make use of anatomical information in PET reconstruction, provided appropriate methods are available.  ...  Acknowledgments This work was supported by grants R01 EB010197, R21 CA149587 and R01 EB013293.  ... 
doi:10.1053/j.semnuclmed.2012.08.006 pmid:23178087 pmcid:PMC3670801 fatcat:kxuwjq6oz5e3vej6wrrywh4bfy

Iterative PET Image Reconstruction Using Convolutional Neural Network Representation [article]

Kuang Gong, Jiahui Guan, Kyungsang Kim, Xuezhu Zhang, Georges El Fakhri, Jinyi Qi, Quanzheng Li
2017 arXiv   pre-print
PET image reconstruction is challenging due to the ill-poseness of the inverse problem and limited number of detected photons.  ...  An innovative feature of the proposed method is that we embed the neural network in the iterative reconstruction framework for image representation, rather than using it as a post-processing tool.  ...  Methods based on sparse representations [21] - [26] , have also shown better image qualities in both static and dynamic reconstructions.  ... 
arXiv:1710.03344v1 fatcat:7jcyfusz5bcnfj7lhlsox5iawy

Hierarchical Patch-Based Sparse Representation—A New Approach for Resolution Enhancement of 4D-CT Lung Data

Yu Zhang, Guorong Wu, Pew-Thian Yap, Qianjin Feng, Jun Lian, Wufan Chen, Dinggang Shen
2012 IEEE Transactions on Medical Imaging  
fashion to reconstruct the final intermediate slices with significantly enhanced anatomical details.  ...  In all experiments, our method outperforms the conventional linear and cubic-spline interpolation methods in preserving image details and also in suppressing misleading artifacts, indicating that our proposed  ...  [33] showed that the high-resolution images can be achieved by using sparse representation. Tosic et al.  ... 
doi:10.1109/tmi.2012.2202245 pmid:22692897 fatcat:jt4fpfknvbeqbe644bfva5ausi

Helical CT Reconstruction from Sparse-view Data through Exploiting the 3D Anatomical Structure Sparsity

Yongbo Wang, Gaofeng Chen, Xi Tao, Zhaoying Bian, Dong Zeng, Habib Zaidi, Ji He, Jianhua Ma
2021 IEEE Access  
To deal with this problem, we analyzed the three-dimensional (3D) anatomical structure sparsity in SHCT images.  ...  In this paper, we show that the sparse-view helical CT (SHCT) images contain not only noise and artifacts but also severe anatomical distortions.  ...  The proposed TDATV method VOLUME 9, Results of patient case 3 reconstructed with different sparse levels. The top and bottom images are reconstructed with the WFBP and TDATV methods, respectively.  ... 
doi:10.1109/access.2021.3049181 fatcat:xu44rurg7jcp7gehhbrd6rijwm

Fusion of Brain PET and MRI Images using Tissue-aware Conditional Generative Adversarial Network with Joint Loss

Jiayin Kang, Wu Lu, Wenjuan Zhang
2020 IEEE Access  
Extensive experiments demonstrate that the proposed method enhances the anatomical details of the fused image while effectively preserving the color information from the PET.  ...  Specifically, the process of fusing brain PET and MRI images is treated as an adversarial machine between retaining the color information of PET and preserving the anatomical information of MRI.  ...  This type of approach first solves the sparse representation coefficients both for PET and for MRI images, respectively; then merges the calculated coefficients via specific fusion rule; lastly reconstructs  ... 
doi:10.1109/access.2019.2963741 fatcat:iomdb7rcmvbyzjfvcab3wpstsa

Semisupervised Tripled Dictionary Learning for Standard-Dose PET Image Prediction Using Low-Dose PET and Multimodal MRI

Yan Wang, Guangkai Ma, Le An, Feng Shi, Pei Zhang, David S. Lalush, Xi Wu, Yifei Pu, Jiliu Zhou, Dinggang Shen
2017 IEEE Transactions on Biomedical Engineering  
Methods-It was achieved by patch-based sparse representation (SR), using the training samples with a complete set of MRI, L-PET and S-PET modalities for dictionary construction.  ...  L-PET) counterpart and corresponding magnetic resonance imaging (MRI).  ...  Acknowledgments This work was supported in part by the National Institutes of Health grants MH100217, AG042599, MH070890, EB006733, EB008374, EB009634, NS055754, MH064065, HD053000, and STMSP PROJECT 2014RZ0027  ... 
doi:10.1109/tbme.2016.2564440 pmid:27187939 pmcid:PMC5383421 fatcat:oa7cdkwdx5crdmbjerls4j6vge
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