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Deep Learning Based Image Reconstruction for Diffuse Optical Tomography
[chapter]
2018
Lecture Notes in Computer Science
Preserved Fulltext
Diffuse optical tomography (DOT) is a relatively new imaging modality that has demonstrated its clinical potential of probing tumors in a non-invasive and affordable way. ...
In this work, we evaluate the use of a deep learning model to reconstruct images directly from their corresponding DOT projection data. ...
We thank NVIDIA Corporation for the donation of Titan X GPUs used in this research and the Natural Sciences and Engineering Research Council of Canada (NSERC) for partial funding. ...
doi:10.1007/978-3-030-00129-2_13
fatcat:znuyz24yafborhjwbkn5we7xhi
Tutorial on the Use of Deep Learning in Diffuse Optical Tomography
2022
Electronics
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This article discusses the current state-of-the-art diffuse optical tomography systems and comprehensively reviews the deep learning algorithms used in image reconstruction. ...
One of the most successful techniques is the application of deep learning algorithms in diffuse optical tomography. ...
Deep Learning Diffuse Optical Tomography Recently deep learning algorithms have been increasingly used to solve diffuse optical tomography problems for biomedical imaging. ...
doi:10.3390/electronics11030305
fatcat:bui7xkzajvaoblrd4ttmw3odua
2020 Index IEEE Transactions on Computational Imaging Vol. 6
2020
IEEE Transactions on Computational Imaging
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., +, TCI 2020 1219-1232
Computed tomography
An End-to-End Deep Network for Reconstructing CT Images Directly From
Sparse Sinograms. ...
., +, TCI 2020 640-651
Image sensors
A Unified Learning-Based Framework for Light Field Reconstruction From
Coded Projections. ...
., +, TCI 2020 125-137 Truncation Correction for X-ray Phase-Contrast Region-of-Interest Tomography. Felsner, L., +, TCI 2020 625-639 ...
doi:10.1109/tci.2021.3054596
fatcat:puij7ztll5ai7alxrmqzsupcny
Front Matter: Volume 10137
2017
Medical Imaging 2017: Biomedical Applications in Molecular, Structural, and Functional Imaging
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Publication of record for individual papers is online in the SPIE Digital Library. SPIEDigitalLibrary.org Paper Numbering: Proceedings of SPIE follow an e-First publication model. ...
seven-digit CID article numbering system structured as follows: The first five digits correspond to the SPIE volume number. The last two digits indicate publication order within the volume using a Base ...
04
X-ray luminescence computed tomography: a sensitivity study [10137-3]
10137 05
A radiative transfer equation-based image-reconstruction method incorporating boundary
conditions for diffuse optical ...
doi:10.1117/12.2277895
dblp:conf/mibam/X17
fatcat:hq5s7pahirdilkfy4pzali4fe4
Deep Learning Can Reverse Photon Migration for Diffuse Optical Tomography
[article]
2017
arXiv
pre-print
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As an example for clinical relevance, we applied the method to our prototype diffuse optical tomography (DOT). ...
Here we propose a novel deep learning approach that learns non-linear photon scattering physics and obtains accurate 3D distribution of optical anomalies. ...
Conclusion In this paper, we proposed a deep learning approach to solve the inverse scattering problem of diffuse optical tomography (DOT). ...
arXiv:1712.00912v1
fatcat:y3wpsbttojdvlk4uudz2n6zmfi
A survey on deep learning in medical image reconstruction
2021
Intelligent Medicine
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Acknowledgements The authors gratefully acknowledge NWO-WOTRO for their financial support. ...
DNNs: deep neural networks; EMT: electromagnetic tomography; DL: deep learning; DOT: diffuse optical tomography Table 7 Deep learning tools. ...
[95] , photoacoustic tomography (PAT) [96] , optical microscopy [97] , diffuse optical tomography (DOT), electromagnetic tomography (EMT) [98] , monocular colonoscopy [99] , holographic image ...
doi:10.1016/j.imed.2021.03.003
fatcat:7orgevbcbvhabnluoforurxvna
Front Matter: Volume 10578
2018
Medical Imaging 2018: Biomedical Applications in Molecular, Structural, and Functional Imaging
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The diverse sessions included MRI and fMRI, Keynote and Emerging Trends, Neurological Imaging, Cardiovascular Imaging, Novel Imaging Techniques and Applications, Innovations in Image Processing, Optical ...
, Cancer, Imaging Agents, and Bone and Musculoskeletal. ...
optical coherence tomography using convolutional
neural networks [10578-69]
10578 1Z
Exploit 18 F-FDG enhanced urinary bladder in PET data for deep learning ground truth
generation in CT scans [10578 ...
doi:10.1117/12.2323952
fatcat:om4wezsn3vgr7mebecadzuy5ly
Learnable Douglas-Rachford iteration and its applications in DOT imaging
2020
Inverse Problems and Imaging
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The DR-Net is applied to solve image reconstruction problem in diffusion optical tomography (DOT), a non-invasive imaging technique with many applications in medical imaging. ...
This paper proposed a deep neural network (DNN) based image reconstruction method, the so-called DR-Net, that leverages the interpretability of existing regularization methods and adaptive modeling capacity ...
The proposed deep learning based image reconstruction method, called DR-Net, is then applied to the challenging image reconstruction problem in DOT imaging. ...
doi:10.3934/ipi.2020031
fatcat:ldu2pbgacfhjncsorbx7j4vvhy
Front Matter: Volume 11521
2020
Biomedical Imaging and Sensing Conference 2020
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Publication of record for individual papers is online in the SPIE Digital Library. SPIEDigitalLibrary.org Paper Numbering: Proceedings of SPIE follow an e-First publication model. ...
seven-digit CID article numbering system structured as follows: § The first five digits correspond to the SPIE volume number. § The last two digits indicate publication order within the volume using a Base ...
coherence tomography imaging (Invited Paper) [11521-20]
11521 0E
Ghost imaging for weak light imaging by using arrival time of photon and deep learning
(Invited Paper) [11521-25]
iii
Proc. of ...
doi:10.1117/12.2574221
fatcat:skdtnhncgnbnhjtwgb42xv3mu4
Front Matter: Volume 10573
2018
Medical Imaging 2018: Physics of Medical Imaging
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The publisher is not responsible for the validity of the information or for any outcomes resulting from reliance thereon. ...
seven-digit CID article numbering system structured as follows: The first five digits correspond to the SPIE volume number. The last two digits indicate publication order within the volume using a Base ...
based on projection domain for low dose CT [10573-130]
10573 3N
Phantom-based field maps for gradient nonlinearity correction in diffusion imaging
[10573-131]
10573 3O
Deep residual learning enabled ...
doi:10.1117/12.2323748
fatcat:mn5csad2mjezljnvzxem3rhk5i
Front Matter: Volume 11317
2020
Medical Imaging 2020: Biomedical Applications in Molecular, Structural, and Functional Imaging
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in Molecular, Structural, and Functional Imaging, Innovations in Image Processing, Neurological Imaging, Novel Imaging Techniques and Applications, Ocular and Optical Imaging, Vascular and Pulmonary Imaging ...
The diverse sessions included Keynote and Invited Talk, Bone and Skeletal Imaging, Segmentation, Registration and Decision-making, Cardiac Imaging and Nanoparticle Imaging, Deep Convolutional Neural Networks ...
diffusion optical tomography image reconstruction for breast imaging [11317-46]
11317 1C
In vivo cancer detection in animal model using hyperspectral image classification with
wavelet feature extraction ...
doi:10.1117/12.2570187
fatcat:5hec55iwfneuhbhtjbqjcf2jqu
Table of Contents
2020
IEEE Transactions on Computational Imaging
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Eldar 666 Collaborative Deep Learning for Super-Resolving Blurry Text Images . . . . . . . Y. Quan, J. Yang, Y. Chen, Y. Xu, and H. ...
Boufounos 1523 Segmentation-Driven Optimization For Iterative Reconstruction in Optical Projection Tomography: An Exploration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ...
doi:10.1109/tci.2021.3054280
fatcat:7se3scatcrcutgat3tpk5mz2nm
A model-based iterative learning approach for diffuse optical tomography
[article]
2021
arXiv
pre-print
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Diffuse optical tomography (DOT) utilises near-infrared light for imaging spatially distributed optical parameters, typically the absorption and scattering coefficients. ...
A more recent trend in image reconstruction techniques is the use of deep learning techniques, which have shown promising results in various applications from image processing to tomographic reconstructions ...
Arridge, "Optical tomography in medical imaging," Inverse Problems, vol. 15, no. 2, p. R41, 1999. ...
arXiv:2104.09579v2
fatcat:byjo4mnnezardbtymhj463cpvu
Front Matter: Volume 11553
2020
Optics in Health Care and Biomedical Optics X
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in tissues 11553 0X
Dual-tracer PET image direct reconstruction and separation based on three-dimensional encoder-decoder network [11553-34]
NANOBIOPHOTONICS
16 Atto-level nanobiophotonic sensing ...
TRANSLATIONAL OPTICAL TECHNIQUES FOR CLINICAL MEDICINE
0T Heptamethine cyanine-based small molecular cancer theranostic agents 11553 0V Quantitative detection of protoporphyrin IX (PpIX) fluorescence ...
of cervical carcinoma cells with deep learning 11553 2K Negativity artifacts analysis in back-projection based photoacoustic tomography 11553 2L Simultaneous algebraic reconstruction technique based ...
doi:10.1117/12.2585933
fatcat:2ajwwhlafzcbtiqtguuhecgstq
Optical aspects of a miniature fluorescence microscope for super-sensitive biomedical detection
2020
Zenodo
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We present optical design and the principle demonstrator of a miniature fluorescence microscope aiming for super-sensitive detection. ...
Current commercial fluorescence microscopes are typically sophisticated, bulky and expensive, not suitable for low-volume or clinic routine biomedical detection. ...
JTh2A.33 Mapping neural correlates to language and biological motion in school-age children with autism using high-density diffuse optical tomography, Alexandra M. ...
doi:10.5281/zenodo.3822435
fatcat:3eoome22a5grbmarbrktphfh7a
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