Filters








707 Hits in 3.3 sec

A Spatiotemporal Agent for Robust Multimodal Registration

Ziwei Luo, Xin Wang, Xi Wu, Youbing Yin, Kunlin Cao, Qi Song, Jing Hu
2020 IEEE Access  
Multimodal image registration is a crucial step for a variety of medical applications to provide complementary information from the combination of various data sources.  ...  Moreover, we propose a customized reward function driven by fixed points error (FPE) to guide the agent to the correct registration direction.  ...  CONCLUSION In this paper, 2D registration is redefined as a 3D sequence learning task. We have presented a multimodal registration approach based on a spatiotemporal agent.  ... 
doi:10.1109/access.2020.2989150 fatcat:yhgerk2w2zc3dkzekmm7iewmgq

Automated registration of magnetic resonance imaging and optoacoustic tomography data for experimental studies

Wuwei Ren, Hlynur Skulason, Felix Schlegel, Markus Rudin, Jan Klohs, Ruiqing Ni
2019 Neurophotonics  
The accuracy and robustness of the registration are improved using a two-step registration method with preprocessing of OAT and MRI data.  ...  Multimodal imaging combining optoacoustic tomography (OAT) with magnetic resonance imaging (MRI) enables spatiotemporal resolution complementarity, improves accurate quantification, and thus yields more  ...  MI-based method was adopted for automated registration for its avoidance of the time-consuming feature extraction task and has proven its robustness in multimodal registration task.  ... 
doi:10.1117/1.nph.6.2.025001 pmid:30989087 pmcid:PMC6446211 fatcat:2y5wpghq5fezxpi5fwp4v4qeh4

Multimodal neuroimaging computing: the workflows, methods, and platforms

Sidong Liu, Weidong Cai, Siqi Liu, Fan Zhang, Michael Fulham, Dagan Feng, Sonia Pujol, Ron Kikinis
2015 Brain Informatics  
Multimodal neuroimaging has become a major driver of current neuroimaging research due to the recognition of the clinical benefits of multimodal data, and the better access to hybrid devices.  ...  Multimodal neuroimaging computing is very challenging, and requires sophisticated computing to address the variations in spatiotemporal resolution and merge the biophysical/biochemical information.  ...  tivecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a  ... 
doi:10.1007/s40708-015-0020-4 pmid:27747508 pmcid:PMC4737665 fatcat:hr5otfj36ngm7pyvbmvzwlyv4q

Recent Technical Advances in Accelerating the Clinical Translation of Small Animal Brain Imaging: Hybrid Imaging, Deep Learning, and Transcriptomics

Wuwei Ren, Bin Ji, Yihui Guan, Lei Cao, Ruiqing Ni
2022 Frontiers in Medicine  
resolution scale in a non-invasively manner.  ...  between biological species regarding brain size, cell type, protein expression level, and metabolism level and (2) imaging technical barriers regarding the interpretation of image contrast and limited spatiotemporal  ...  The accuracy and robustness of such DL-based registration have been shown to be comparable with classic methods but at a much higher speed without manual efforts on either landmark selection or boundary  ... 
doi:10.3389/fmed.2022.771982 pmid:35402436 pmcid:PMC8987112 fatcat:63egkkymnfcixj6piv4tnkl73m

Quantitative assessment of intra‐ and inter‐modality deformable image registration of the heart, left ventricle, and thoracic aorta on longitudinal 4D‐CT and MR images

Alireza Omidi, Elisabeth Weiss, John S. Wilson, Mihaela Rosu‐Bubulac
2021 Journal of Applied Clinical Medical Physics  
Heart and TA demonstrated higher registration accuracy compared to LV for all scenarios except for HD and Dice values in Group A.  ...  Each organ underwent three intramodal DIRs ((A) CT modality over time, (B) MR modality over time, and (C) MR contrast effect at the same time) and two intermodal DIRs ((D) CT/MR multimodality at same time  ...  time, and Group E: CT/MR multimodality over time Table 1 1 summarizes the data available for each •, contrast agent 18 ml gadopentetate dimeglumine.  ... 
doi:10.1002/acm2.13500 pmid:34962065 pmcid:PMC8833287 fatcat:bjyc7b772vewbk6abtfhi3jpnm

Associations between Tumor Vascularity, Vascular Endothelial Growth Factor Expression and PET/MRI Radiomic Signatures in Primary Clear-Cell–Renal-Cell-Carcinoma: Proof-of-Concept Study

Qingbo Yin, Sheng-Che Hung, Li Wang, Weili Lin, Julia R. Fielding, W. Kimryn Rathmell, Amir H. Khandani, Michael E. Woods, Matthew I. Milowsky, Samira A. Brooks, Eric. M. Wallen, Dinggang Shen
2017 Scientific Reports  
Also, tumor angiogenesis is an important prognostic factor of clear cell renal cell carcinoma (ccRCC), as well as a factor in guiding treatment with antiangiogenic agents.  ...  Studies have shown that tumor angiogenesis is an essential process for tumor growth, proliferation and metastasis.  ...  The FLIRT tool (FMRIB's Linear Image Registration Tool), a fully automated robust and accurate tool, was used for linear (affine) intra-and inter-modal image registration, which has been extensively and  ... 
doi:10.1038/srep43356 pmid:28256615 pmcid:PMC5335708 fatcat:d7mw7nkbffcx7accsikzbdhdny

A survey on deep multimodal learning for computer vision: advances, trends, applications, and datasets

Khaled Bayoudh, Raja Knani, Fayçal Hamdaoui, Abdellatif Mtibaa
2021 The Visual Computer  
We also survey current multimodal applications and present a collection of benchmark datasets for solving problems in various vision domains.  ...  Extracting relevant patterns from this kind of data is still a motivating goal for researchers in deep learning.  ...  In summary, the multimodal RNN model is a robust tool for analyzing both short-and long-term dependencies of multimodal data sequences using the backpropagation algorithm.  ... 
doi:10.1007/s00371-021-02166-7 pmid:34131356 pmcid:PMC8192112 fatcat:jojwyc6slnevzk7eaiutlmlgfe

Deep Learning for Medical Image Registration: A Comprehensive Review [article]

Subrato Bharati, M. Rubaiyat Hossain Mondal, Prajoy Podder, V. B. Surya Prasath
2022 arXiv   pre-print
This review focuses on monomodal and multimodal registration and associated imaging, for instance, X-ray, CT scan, ultrasound, and MRI.  ...  Firstly, a discussion is provided for supervised registration categories, for example, fully supervised, dual supervised, and weakly supervised registration.  ...  Multimodal image registrations, such as those involving TRUS and MRI, face similar challenges, such as the inability to use a robust similarity metric for multimodal applications, the lack of large datasets  ... 
arXiv:2204.11341v1 fatcat:n6yacnk3ffdallbeirsgqpj274

2020 Index IEEE Transactions on Automation Science and Engineering Vol. 17

2020 IEEE Transactions on Automation Science and Engineering  
Prorok, A., TASE Oct. 2020 2025-2037 Robust Generalized Point Cloud Registration With Orientational Data Based on Expectation Maximization.  ...  ., +, TASE April 2020 909-920 Multi-agent systems Design, Application, and Evaluation of a Multiagent System in the Logistics Domain.  ...  ., +, TASE Jan. 2020 41-55 PROLOG A System Architecture for CAD-Based Robotic Assembly With Sensor-Based Skills.  ... 
doi:10.1109/tase.2020.3037603 fatcat:kyt63444lfc45amrjebyjw34qu

Computational Analysis: A Bridge to Translational Stroke Treatment [chapter]

Nirmalya Ghosh, Yu Sun, Christine Turenius, Bir Bhanu, Andre Obenaus, Stephen Ashwal
2012 Translational Stroke Research  
, and a watershed method that are robust at different developmental stages.  ...  We provide a summary of current computational approaches used for injury detection, including Gaussian mixture models (GMM), Markov random fi elds (MRFs), normalized graph cut, and K-means clustering.  ...  Such atlases can be developed separately for a particular MR modality (e.g., T2WI, ADC, Diffusion Tensor Imaging, etc.) or images from different modalities can be registered (multimodal registration) to  ... 
doi:10.1007/978-1-4419-9530-8_42 fatcat:did4nx25jzgkjjt4onmamkytjm

Computer Vision in Healthcare Applications

Junfeng Gao, Yong Yang, Pan Lin, Dong Sun Park
2018 Journal of Healthcare Engineering  
First, integration of multimodal information carried out from different diagnostic imaging techniques is essential for a comprehensive characterization of the region under examination.  ...  the spatial domain (2D) to the spatiotemporal domain (3D) that is designed for multiplicative noise suppression, specifically for ultrasound image and video filtering.  ... 
doi:10.1155/2018/5157020 pmid:29686826 pmcid:PMC5857319 fatcat:nouvaymmrbgircnal6irb2nynq

Multimodal neuroimaging computing: a review of the applications in neuropsychiatric disorders

Sidong Liu, Weidong Cai, Siqi Liu, Fan Zhang, Michael Fulham, Dagan Feng, Sonia Pujol, Ron Kikinis
2015 Brain Informatics  
We also outline some future directions for multimodal neuroimaging where researchers will design more advanced methods and models for neuropsychiatric research.  ...  One of the most important applications of multimodal neuroimaging is the provision of vital diagnostic data for neuropsychiatric disorders.  ...  tivecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a  ... 
doi:10.1007/s40708-015-0019-x pmid:27747507 pmcid:PMC4737664 fatcat:6tbjyaq6znfrbazefmm3af3x5a

Front Matter: Volume 9788

2016 Medical Imaging 2016: Biomedical Applications in Molecular, Structural, and Functional Imaging  
The publisher is not responsible for the validity of the information or for any outcomes resulting from reliance thereon.  ...  using a Base 36 numbering system employing both numerals and letters.  ...  brain visualization [9788-69] 9788 1Z Comparative study of multimodal intra-subject image registration methods on a publicly available database [9788-70] 9788 20 Automated tissue classification  ... 
doi:10.1117/12.2240426 dblp:conf/mibam/X16 fatcat:msxwbg54kbegriwgvgcw4dnzu4

Early role of vascular dysregulation on late-onset Alzheimer's disease based on multifactorial data-driven analysis

Y. Iturria-Medina, R. C. Sotero, P. J. Toussaint, J. M. Mateos-Pérez, A. C. Evans, Michael W. Weiner, Paul Aisen, Ronald Petersen, Clifford R. Jack, William Jagust, John Q. Trojanowki, Arthur W. Toga (+303 others)
2016 Nature Communications  
Through a multifactorial data-driven analysis, we obtain dynamic LOAD-abnormality indices for all biomarkers, and a tentative temporal ordering of disease progression.  ...  High abnormality levels are also observed for specific proteins associated with the vascular system's integrity.  ...  Acknowledgements We are grateful to Mélissa Savard and Joshua Morse for their helpful suggestions and comments on the manuscript. This study was partially supported by Brain Canada  ... 
doi:10.1038/ncomms11934 pmid:27327500 pmcid:PMC4919512 fatcat:ozbuzdl435buja3hied35gj5sm

Photoacoustic-MR Image Registration Based on a Co-Sparse Analysis Model to Compensate for Brain Shift

Parastoo Farnia, Bahador Makkiabadi, Maysam Alimohamadi, Ebrahim Najafzadeh, Maryam Basij, Yan Yan, Mohammad Mehrmohammadi, Alireza Ahmadian
2022 Sensors  
In this study, the co-sparse analysis model is proposed for photoacoustic-MR image registration, which can capture the interdependency of the two modalities.  ...  Finding a satisfactory registration method is challenging due to the unpredictable nature of brain deformation.  ...  Acknowledgments: The authors gratefully acknowledge Ruiqing Ni from the University of Zurich and ETH Zurich for providing mouse brain data.  ... 
doi:10.3390/s22062399 pmid:35336570 pmcid:PMC8954240 fatcat:qgui22ylgbe3lgxmz4ueofceb4
« Previous Showing results 1 — 15 out of 707 results