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Can Deep Learning Outperform Modern Commercial CT Image Reconstruction Methods? [article]

Hongming Shan, Atul Padole, Fatemeh Homayounieh, Uwe Kruger, Ruhani Doda Khera, Chayanin Nitiwarangkul, Mannudeep K. Kalra, Ge Wang
2018 arXiv   pre-print
Here we design a novel neural network architecture for low-dose CT (LDCT) and compare it with commercial iterative reconstruction methods used for standard of care CT.  ...  While popular neural networks are trained for end-to-end mapping, driven by big data, our novel neural network is intended for end-to-process mapping so that intermediate image targets are obtained with  ...  The main motivation of this study is to demonstrate whether deep neural networks perform better than the modern commercial iterative reconstruction methods for LDCT and establish a foundation for CT reconstruction  ... 
arXiv:1811.03691v1 fatcat:75zgv47hbzdajptylxzvhms7ee

Synergizing medical imaging and radiotherapy with deep learning

Hongming Shan, Xun Jia, Pingkun Yan, Yunyao Li, Harald Paganetti, Ge Wang
2020 Machine Learning: Science and Technology  
This article reviews deep learning methods for medical imaging (focusing on image reconstruction, segmentation, registration, and radiomics) and radiotherapy (ranging from planning and verification to  ...  It is believed that deep learning in particular, and artificial intelligence and machine learning in general, will have a revolutionary potential to advance and synergize medical imaging and radiotherapy  ...  Originally designed for a low dose CT reconstruction challenge, the Mayo low dose CT dataset contains perfectly registered low dose and normal dose CT scans, and has became a benchmark dataset in deep  ... 
doi:10.1088/2632-2153/ab869f fatcat:aibfmfelcngkrk4ilwcs25c77a

On Interpretability of Artificial Neural Networks: A Survey [article]

Fenglei Fan, Jinjun Xiong, Mengzhou Li, Ge Wang
2021 arXiv   pre-print
Due to the huge potential of deep learning, interpreting neural networks has recently attracted much research attention.  ...  Deep learning as represented by the artificial deep neural networks (DNNs) has achieved great success in many important areas that deal with text, images, videos, graphs, and so on.  ...  The authors are grateful for Dr. Hongming Shan's suggestions (Fudan University) and anonymous reviewers' advice.  ... 
arXiv:2001.02522v4 fatcat:pxa66n2wfjcbxfwc3k5gm3r2xa

EPSM 2020, Engineering and Physical Sciences in Medicine

2021 Physical and Engineering Sciences in Medicine  
Limited experience in conducting online exams resulted in a steep learning curve to identify methods to assure academic integrity.  ...  The clinical community is urged to identify methods to facilitate the early return of hospital-based teaching to prepare future TEAP registrars with the appropriate foundational education.  ...  Acknowledgements The authors want to thank iRT for loan of the IQM transmission detector system and their support during installation and initial test of the system.  ... 
doi:10.1007/s13246-021-01024-z pmid:34424484 pmcid:PMC8381140 fatcat:7jrqj62qgzhcxaiztb627teqxe

CARS 2020—Computer Assisted Radiology and Surgery Proceedings of the 34th International Congress and Exhibition, Munich, Germany, June 23–27, 2020

2020 International Journal of Computer Assisted Radiology and Surgery  
Aiming to stimulate complimentary thoughts and actions on what is being presented at CARS, implies a number of enabling variables for optimal analogue scholarly communication, such as (examples given are  ...  In the times of COVID-19 overshadowing CARS 2020 and what the future may hold, a CARS meeting with these numbers of participants is not feasible anymore and new ways have to be explored to still fulfill  ...  Besides, use of gloves is low, so doses of hands are still high. Therefore, a master-slave robotic system for VI is necessary for minimization of the radiation exposure.  ... 
doi:10.1007/s11548-020-02171-6 pmid:32514840 fatcat:lyhdb2zfpjcqbf4mmbunddwroq

Deep Learning for Lung Cancer Nodules Detection and Classification in CT Scans

Diego Riquelme, Moulay A. Akhloufi
2020 AI  
In this work, we review recent state-of-the-art deep learning algorithms and architectures proposed as CAD systems for lung cancer detection.  ...  Nowadays, researchers are trying different deep learning techniques to increase the performance of CAD systems in lung cancer screening with computed tomography.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/ai1010003 fatcat:k7mj3cdzovhhpkxknm34zsw7c4

A Model for Online Interactive Remote Education for Medical Physics Using the Internet

Milton K Woo, Kwan-Hoong Ng
2003 Journal of Medical Internet Research  
We will also provide a basic understanding of some most widely used reconstruction algorithms by focusing on the image reconstruction problem in X-ray CT.  ...  Simulations of the detector signal for selected sample dose distributions were performed and used to verify the range of reliability for the reconstruction algorithm.  ...  In operation images are available for viewing in less than a minute. Preliminary work imaging volunteers demonstrates that the performance of the system is generally comparable to film.  ... 
doi:10.2196/jmir.5.1.e3 pmid:12746208 pmcid:PMC1550549 fatcat:tsyf45yusza2jiglkq62rgo3qm

Power pulsing of the CALICE tile hadron calorimeter

Mathias Reinecke
2016 2016 IEEE Nuclear Science Symposium, Medical Imaging Conference and Room-Temperature Semiconductor Detector Workshop (NSS/MIC/RTSD)  
DUNE consists of an intense neutrino beam fired a distance of 1300 km from Fermilab (near Chicago) to the 40,000 ton Liquid Argon DUNE detector, located deep underground in the Homestake mine.  ...  This achievement was recognised through the award of the 2015 Nobel prize for physics to the leaders of the SNO and Super-Kamiokande experiments for the conclusive establishment of the phenomenon of neutrino  ...  M13A-9: A Direct Image Reconstruction Algorithm for PET Scanners Based on Monolithic Crystals Acknowledgments: This work was done as part of the INSERT collaboration, which is supported by the EC: FP7-  ... 
doi:10.1109/nssmic.2016.8069748 fatcat:zjgd7dmfdbhntb4kfwdtrlejhi

Artificial Intelligence: Research Impact on Key Industries; the Upper-Rhine Artificial Intelligence Symposium (UR-AI 2020) [article]

Andreas Christ, Franz Quint
2020 arXiv   pre-print
The TriRhenaTech alliance presents a collection of accepted papers of the cancelled tri-national 'Upper-Rhine Artificial Inteeligence Symposium' planned for 13th May 2020 in Karlsruhe.  ...  The TriRhenaTech alliance is a network of universities in the Upper-Rhine Trinational Metropolitan Region comprising of the German universities of applied sciences in Furtwangen, Kaiserslautern, Karlsruhe  ...  The author is responsible for the content of this publication. Acknowledgments Underlying projects to this article are funded by the WTD 81 of the German Federal Ministry of Defense.  ... 
arXiv:2010.16241v1 fatcat:y6lc2dmlyvh55bw2ytfbf7hwta

2021 Index IEEE Transactions on Instrumentation and Measurement Vol. 70

2021 IEEE Transactions on Instrumentation and Measurement  
Departments and other items may also be covered if they have been judged to have archival value. The Author Index contains the primary entry for each item, listed under the first author's name.  ...  The primary entry includes the coauthors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, and article number.  ...  ., +, TIM 2021 4504611 Tensor Gradient L 0 -Norm Minimization-Based Low-Dose CT and Its Appli-cation to COVID-19.  ... 
doi:10.1109/tim.2022.3156705 fatcat:dmqderzenrcopoyipv3v4vh4ry

State of the art in total body PET

Stefaan Vandenberghe, Pawel Moskal, Joel S. Karp
2020 EJNMMI Physics  
These results illustrate the large potential of this concept with regard to low-dose imaging, faster scanning, whole-body dynamic imaging and follow-up of tracers over longer periods.  ...  The gains for single organ (compared to a fully 3D PET 20-cm axial FOV) are limited to a factor 3-4.  ...  Acknowledgements The authors would like to thank Maya Akl Abi from Texas AM University at Qatar for providing the NECR plots and Dr.  ... 
doi:10.1186/s40658-020-00290-2 pmid:32451783 fatcat:57h4hxlhefc6tdlbjdh4kbovt4

Artificial Intellgence – Application in Life Sciences and Beyond. The Upper Rhine Artificial Intelligence Symposium UR-AI 2021 [article]

Karl-Herbert Schäfer
2021 arXiv   pre-print
The TriRhenaTech alliance is a network of universities in the Upper-Rhine Trinational Metropolitan Region comprising of the German universities of applied sciences in Furtwangen, Kaiserslautern, Karlsruhe  ...  The alliance's common goal is to reinforce the transfer of knowledge, research, and technology, as well as the cross-border mobility of students.  ...  Acknowledgements The authors would like to thank D. Iordanov for the contribution to the development of the application within his studies at Mainz University of Applied Sciences.  ... 
arXiv:2112.05657v1 fatcat:wdjgymicyrfybg5zth2dc2i3ni

Proceedings of the World Molecular Imaging Congress 2019, Montreal Quebec, Canada September 4-7, 2019: Late-Breaking Abstracts

2019 Molecular Imaging and Biology  
The goal of this pre-clinical study was to develop a Multiparametric Advanced Fast Imaging (MAFI) approach for rapid and sensitive localization of intracranial tumors and characterization of tumor "habitat  ...  We further hope to expand our MAFI MRI capacity by performing macrophage-specific T2/T2*-MRI (inflammation) and diffusion-weighted imaging (DWI for edema and necrosis) as reliable predictors for radiation  ...  Methods: Previously segmented T2 weighted mri images of the colon in mice from studies of dextran sodium sulfate (DSS) induced colitis were used to train and validate a convolutional neural network (CNN  ... 
doi:10.1007/s11307-019-01453-z pmid:31745759 pmcid:PMC7103224 fatcat:qg26keokzzf57olialmadji72m

A Survey of FPGA-Based Robotic Computing [article]

Zishen Wan, Bo Yu, Thomas Yuang Li, Jie Tang, Yuhao Zhu, Yu Wang, Arijit Raychowdhury, Shaoshan Liu
2021 arXiv   pre-print
An analysis of software and hardware optimization techniques and main technical issues is presented, along with some commercial and space applications, to serve as a guide for future work.  ...  However, the high computation and data complexity of robotic algorithms pose great challenges to its applications. On the one hand, CPU platform is flexible to handle multiple robotic tasks.  ...  Most state-of-the-art algorithms now apply one type of neural network based on convolution operation.  ... 
arXiv:2009.06034v3 fatcat:fnp5q5wcyrd2hgpllso22mv2xm

Proceedings of the World Molecular Imaging Congress 2021, October 5-8, 2021: General Abstracts

2022 Molecular Imaging and Biology  
An efficient rapidly converging deconvolution algorithm with a novel resolution subsets-based approach RSEMD for improving the quantitative accuracy of previously reconstructed clinical MRI images by commercial  ...  Data acquisition was performed on a commercial Siemens MRI system.  ...  The nanocluster system with a high selectivity showed the potential for fluorescence imaging and the integrating of gold and MMAE demonstrated excellent concurrent chemotherapy-radiotherapy efficacy, which  ... 
doi:10.1007/s11307-021-01693-y pmid:34982365 pmcid:PMC8725635 fatcat:4sfb3isoyfdhfbiwxfr55gvqym
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