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Robust PCA Unrolling Network for Super-resolution Vessel Extraction in X-ray Coronary Angiography [article]

Binjie Qin, Haohao Mao, Yiming Liu, Jun Zhao, Yisong Lv, Yueqi Zhu, Song Ding, Xu Chen
2022 arXiv   pre-print
Therefore, we propose a novel robust PCA unrolling network with sparse feature selection for super-resolution XCA vessel imaging.  ...  prune complex vessel-like artefacts and noisy backgrounds in XCA during network training but also iteratively learn and select the high-level spatiotemporal semantic information of moving contrast agents  ...  ACKNOWLEDGEMENTS The authors thank all the cited authors for providing the source codes used in this work and the anonymous reviewers for their valuable comments on the manuscript.  ... 
arXiv:2204.08466v2 fatcat:msgakedt4na6xmgzokaskno25a

Table of Contents

2020 2020 IEEE International Conference on Image Processing (ICIP)  
... 2196 -LD ;X <LPLQJ /L <RQJ -LDQJ 6KXWDR ;LD 7VLQJKXD 8QLYHUVLW\ &KLQD ARS-18: MACHINE LEARNING FOR RECOGNITION IN IMAGES AND VIDEOS II ARS-18.1: CNN-ASSISTED COVERINGS IN THE SPACE OF TILTS: BEST AFFINE  ...  TEC-04.15: WEAKLY-SUPERVISED DEFECT SEGMENTATION WITHIN VISUAL .................................................... 743 INSPECTION IMAGES OF LIQUID CRYSTAL DISPLAYS IN ARRAY PROCESS )$1 /, *824,$1* +8  ...  SEGMENTATION AND 3D RECONSTRUCTION OF NON-RIGID SHAPE ................................................ ................................  ... 
doi:10.1109/icip40778.2020.9191006 fatcat:3fkxl2sjmre2jkryewwo5mlahi

Digital Image Processing for Ophthalmology: Detection of the Optic Nerve Head

Xiaolu Zhu, Rangaraj M. Rangayyan, Anna L. Ells
2011 Synthesis Lectures on Biomedical Engineering  
In fundus images, the ONH usually appears as a bright region, white or yellow in color, and is indicated as the convergent area of the network of blood vessels.  ...  Different types of retinal pathology may be detected and analyzed via the application of appropriately designed techniques of digital image processing and pattern recognition.  ...  Acknowledgments The research work described in this book was supported by the Natural Sciences and Engineering Research Council of Canada. We thank Dr. Fábio J.  ... 
doi:10.2200/s00335ed1v01y201102bme040 fatcat:kyjg2sx45ng6pphyya5v4bn5k4

Zero-Shot Learning and its Applications from Autonomous Vehicles to COVID-19 Diagnosis: A Review

Mahdi Rezaei, Mahsa Shahidi
2020 Intelligence-Based Medicine  
One of the major issues in deep learning based methodologies such as in Medical Imaging and other real-world applications is the requirement of large annotated datasets prepared by clinicians or experts  ...  This makes the ZSL applicable in many real-world scenarios, from unknown object detection in autonomous vehicles to medical imaging and unforeseen diseases such as COVID-19 Chest X-Ray (CXR) based diagnosis  ...  [1] employs a class decomposition mechanism in DeTraC [2] which is a deep convolutional network that can handle image dataset irregularities of the X-ray images.  ... 
doi:10.1016/j.ibmed.2020.100005 pmid:33043311 pmcid:PMC7531283 fatcat:qzyaf7gpufhermyg5gvank5cja

Zero-Shot Learning and its Applications from Autonomous Vehicles to COVID-19 Diagnosis: A Review

Mahdi Rezaei, Mahsa Shahidi
2020 Social Science Research Network  
One of the major issues in deep learning based methodologies such as in Medical Imaging and other real-world applications is the requirement of large annotated datasets prepared by clinicians or experts  ...  This makes the ZSL applicable in many real-world scenarios, from unknown object detection in autonomous vehicles to medical imaging and unforeseen diseases such as COVID-19 Chest X-Ray (CXR) based diagnosis  ...  [1] employs a class decomposition mechanism in DeTraC [2] which is a deep convolutional network that can handle image dataset irregularities of the X-ray images.  ... 
doi:10.2139/ssrn.3624379 fatcat:yifnxv46rjf6pgndowkxzmo5o4

Learning Neural Textual Representations for Citation Recommendation

Binh Thanh Kieu, Inigo Jauregi Unanue, Son Bao Pham, Hieu Xuan Phan, Massimo Piccardi
2021 2020 25th International Conference on Pattern Recognition (ICPR)  
462 Semi-Supervised Domain Adaptation Via Selective Pseudo Labeling and Progressive Self-Training DAY 4 -Jan 15, 2021 Mitsuno, Kakeru; Kurita, Takio 466 Filter Pruning Using Hierarchical Group Sparse  ...  the Obituaries of Australians Killed in Action in WWI and WWII DAY 2 -Jan 13, 2021 Huang, Danqing; Wang, Jinpeng; Wang, Guoxin; Lin, Chin-Yew 2099 Visual Style Extraction from Chart Images for  ... 
doi:10.1109/icpr48806.2021.9412725 fatcat:3vge2tpd2zf7jcv5btcixnaikm

2021 Index IEEE Transactions on Instrumentation and Measurement Vol. 70

2021 IEEE Transactions on Instrumentation and Measurement  
-that appeared in this periodical during 2021, and items from previous years that were commented upon or corrected in 2021.  ...  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.  ...  Grassini, S., +, TIM 2021 0800303 fication of Glaucoma Stages From Fundus Images.  ... 
doi:10.1109/tim.2022.3156705 fatcat:dmqderzenrcopoyipv3v4vh4ry

Graph Convolutional Networks for Multi-modality Medical Imaging: Methods, Architectures, and Clinical Applications [article]

Kexin Ding, Mu Zhou, Zichen Wang, Qiao Liu, Corey W. Arnold, Shaoting Zhang, Dimitri N. Metaxas
2022 arXiv   pre-print
In this review, we present recent GCNs developments in the context of medical image analysis including imaging data from radiology and histopathology.  ...  We discuss the fast-growing use of graph network architectures in medical image analysis to improve disease diagnosis and patient outcomes in clinical practice.  ...  presents its usefulness for classifying lung cancer subtypes in histopathological images (Adnan et al.) via patch selection.  ... 
arXiv:2202.08916v3 fatcat:zskcqvgjpnb6vdklmyy5rozswq

A combined local and global motion estimation and compensation method for cardiac CT

Qiulin Tang, Beshan Chiang, Akinola Akinyemi, Alexander Zamyatin, Bibo Shi, Satoru Nakanishi, Bruce R. Whiting, Christoph Hoeschen
2014 Medical Imaging 2014: Physics of Medical Imaging  
information. 9034-60, Session PSMon Comparative study of two sparse multinomial logistic regression models in decoding visual stimuli from brain activity of fMRI Abstract: Recently, sparse algorithms  ...  The observer data were analyzed in terms of the correlations between the observer ranking order and the algorithmic ranking order, inter-observer variations, and acceptable ranges.  ...  2 cm) in tens of minutes yielding images containing millions of spectra. Spectra are then automatically classified as one of seven cell-types in prostate tissue in a matter of seconds.  ... 
doi:10.1117/12.2043492 fatcat:fyzpc5m6jbh7fjohqpdmtzkhte

Table of Contents

2020 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI)  
Aggarwal, Hemant Kumar (University of Iowa), Jacob, Mathews (University of Iowa) 15:45-16:00 MoPaO1.6 Adaptive Locally Low Rank and Sparsity Constrained Reconstruction for Accelerated Dynamic Mri  ...  MoPbPo-02.8 Longitudinal Analysis of Mild Cognitive Impairment Via Sparse Smooth Network and Attention-Based Stacked Bi-Directional Long Short Term Memory, pp. 1048-1051.  ... 
doi:10.1109/isbi45749.2020.9098467 fatcat:6kxbkb2s5bdc5cmjvxjhotccay

Intelligent, smart and scalable cyber-physical systems

V. Vijayakumar, V. Subramaniyaswamy, Jemal Abawajy, Longzhi Yang, V. Vijayakumar, V. Subramaniyaswamy, Jemal Abawajy, Longzhi Yang
2019 Journal of Intelligent & Fuzzy Systems  
Components of an iCPS must have a high degree of autonomy while cooperating with each other in a robust, scalable and decentralized way.  ...  As CPSs hold strong interactions between the cyber and physical components, it plays a significant role in the development of next-generation efficient-smart systems in various real-time applications.  ...  Acknowledgments The guest editors would like to thank all reviewers for their efforts in reviewing manuscripts submitted to this special issue. We also thank the Editor-in-Chief, Dr.  ... 
doi:10.3233/jifs-179108 fatcat:4hghoxr4prccxjpfg5juwzoie4

Graph-Based Deep Learning for Medical Diagnosis and Analysis: Past, Present and Future [article]

David Ahmedt-Aristizabal, Mohammad Ali Armin, Simon Denman, Clinton Fookes, Lars Petersson
2021 arXiv   pre-print
In this survey, we thoroughly review the different types of graph architectures and their applications in healthcare.  ...  We provide an overview of these methods in a systematic manner, organized by their domain of application including functional connectivity, anatomical structure and electrical-based analysis.  ...  [29] combined both the fundus image sequence and FA image as input for artery and vein classification.  ... 
arXiv:2105.13137v1 fatcat:gm7d2ziagba7bj3g34u4t3k43y

Exploring deep learning-based architecture, strategies, applications and current trends in generic object detection: A comprehensive review

Lubna Aziz, Sah bin Haji Salam, Sara Ayub
2020 IEEE Access  
Medical images such as retinal (fundus) images and speech patterns may help identify the risk of heart disease.  ...  Some selected images of the benchmark dataset shown in FIGURE 15 and Table IV summarize the specification and attributes of these datasets.  ... 
doi:10.1109/access.2020.3021508 fatcat:guri46oiejhfzeitxuuprpmjka

CARS 2021: Computer Assisted Radiology and Surgery Proceedings of the 35th International Congress and Exhibition Munich, Germany, June 21–25, 2021

2021 International Journal of Computer Assisted Radiology and Surgery  
The methods used in [2] were used to produce distance maps for the reduced data to show the presence of benign and malignant tissue in each image via multivariate analysis of the reduced data.  ...  Statistical comparison via MI of the distance methods are presented in Table 2 .  ...  Artificial intelligence coronary calcium scoring in low dose chest CT-Ready to go?  ... 
doi:10.1007/s11548-021-02375-4 pmid:34085172 fatcat:6d564hsv2fbybkhw4wvc7uuxcy

A Systematic Review on Healthcare Analytics: Application and Theoretical Perspective of Data Mining

Md Islam, Md Hasan, Xiaoyi Wang, Hayley Germack, Md Noor-E-Alam
2018 Healthcare  
Critical elements of the selected studies-healthcare sub-areas, data mining techniques, types of analytics, data, and data sources-were extracted to provide a systematic view of development in this field  ...  Lack of prescriptive analytics in practice and integration of domain expert knowledge in the decision-making process emphasizes the necessity of future research.  ...  They used feature selection via supervised model construction (FSSMC) to select the important factors with rank/order.  ... 
doi:10.3390/healthcare6020054 pmid:29882866 pmcid:PMC6023432 fatcat:xkq4mkqbprabvipxnmcvk3hr6m
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