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Deep Learning Based Image Reconstruction for Diffuse Optical Tomography [chapter]

Hanene Ben Yedder, Aïcha BenTaieb, Majid Shokoufi, Amir Zahiremami, Farid Golnaraghi, Ghassan Hamarneh
2018 Lecture Notes in Computer Science  
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

Ganesh M. Balasubramaniam, Ben Wiesel, Netanel Biton, Rajnish Kumar, Judy Kupferman, Shlomi Arnon
2022 Electronics  
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  
., +, 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  
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]

Jaejun Yoo, Sohail Sabir, Duchang Heo, Kee Hyun Kim, Abdul Wahab, Yoonseok Choi, Seul-I Lee, Eun Young Chae, Hak Hee Kim, Young Min Bae, Young-wook Choi, Seungryong Cho, Jong Chul Ye
2017 arXiv   pre-print
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

Emmanuel Ahishakiye, Martin Bastiaan Van Gijzen, Julius Tumwiine, Ruth Wario, Johnes Obungoloch
2021 Intelligent Medicine  
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

Barjor Gimi, Andrzej Krol
2018 Medical Imaging 2018: Biomedical Applications in Molecular, Structural, and Functional Imaging  
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

Jiulong Liu, ,Department of Mathematics, National University of Singapore, Singapore 119076, Nanguang Chen, Hui Ji, ,Department of Biomedical Engineering, National University of Singapore, Singapore 117583
2020 Inverse Problems and Imaging  
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

Osamu Matoba, Yasuhiro Awatsuji, Yuan Luo, Toyohiko Yatagai, Yoshihisa Aizu
2020 Biomedical Imaging and Sensing Conference 2020  
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

Guang-Hong Chen, Joseph Y. Lo, Taly Gilat Schmidt
2018 Medical Imaging 2018: Physics of Medical Imaging  
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

Barjor S. Gimi, Andrzej Krol
2020 Medical Imaging 2020: Biomedical Applications in Molecular, Structural, and Functional Imaging  
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  
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]

Meghdoot Mozumder, Andreas Hauptmann, Ilkka Nissilä, Simon R. Arridge, Tanja Tarvainen
2021 arXiv   pre-print
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

Qingming Luo, Xingde Li, Ying Gu, Dan Zhu
2020 Optics in Health Care and Biomedical Optics X  
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

Yunfeng Nie, Aikio Sanna, Annukka Kokkonen, Teemu Sipola, Uusitalo Sanna, Simonetta Grilli, Heidi Ottevaere
2020 Zenodo  
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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