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Special Issue on "Machine Learning/Deep Learning in Medical Image Processing"

Mizuho Nishio
2021 Applied Sciences  
Many recent studies on medical image processing have involved the use of machine learning (ML) and deep learning (DL) [...]  ...  applied sciences Editorial Special Issue onMachine Learning/Deep Learning in Medical Image Processing” Mizuho Nishio Department of Diagnostic  ...  This special issue, “Machine Learning/Deep Learning in Medical Image Processing”, has been launched to provide an opportunity for researchers in the area of medical  ... 
doi:10.3390/app112311483 fatcat:tzefkvwvjzcy3gpn2sw6raxlmi

MULTIPLEXING IN MEDICAL IMAGE PROCESSING WITH MACHINE LEARNING METHODS BASED ON RDH

2021 International Journal of Biology Pharmacy and Allied Sciences  
The research created a novel reversible data hiding (RDH) strategy for disease diagnosis depending on Code Division Multiplexing (CDM) as well as machine learning techniques.  ...  The hidden information was embedded further into mid-frequency subcarriers of the ct images using CDM plus machine learning techniques after the patient records picture was translated into a spectral domain  ...  The Small-Sample Neural Network Principle IJBPAS, November, Special Issue, 2021, 10(11) Small-sample neural networks are indeed a common machine learning method for optimizing the process parameters for  ... 
doi:10.31032/ijbpas/2021/10.11.1045 fatcat:li6sg5umizdvzia67bb72k5dy4

Machine Learning in Medical Imaging

Kenji Suzuki, Pingkun Yan, Fei Wang, Dinggang Shen
2012 International Journal of Biomedical Imaging  
The special issue starts by a review of studies on a class of machine-learning techniques, called pixel/voxel-based machine learning, in medical imaging by K.  ...  The special issue was planned in conjunction with the International Workshop on Machine Learning in Medical Imaging (MLMI 2010) [1] , which was the first workshop on this topic, held at the 13th International  ... 
doi:10.1155/2012/123727 pmid:22481902 pmcid:PMC3303553 fatcat:pqx2vz7ubjaebhjivkgiin5aje

Machine learning in medical imaging

Pingkun Yan, Kenji Suzuki, Fei Wang, Dinggang Shen
2013 Machine Vision and Applications  
The special issue was planned in conjunction with the International Workshop on Machine Learning in Medical Imaging 2011 [1] .  ...  The majority of the papers included in this special issue were presented in a preliminary form at the International Workshop on Machine Learning in Medical Imaging, held in Toronto, Canada on September  ... 
doi:10.1007/s00138-013-0543-8 fatcat:j7vpc2imobahzbgopqoifqj6mi

Machine Learning for Medical Imaging

Geng-Shen Fu, Yuri Levin-Schwartz, Qiu-Hua Lin, Da Zhang
2019 Journal of Healthcare Engineering  
An active research topic is how to optimize the transfer of human knowledge to a machine-learning model. is special issue focuses on applying machine-learning techniques to medical imaging data and covers  ...  More recently, machine-learning techniques have been applied to the field of medical imaging [5, 6] .  ... 
doi:10.1155/2019/9874591 pmid:31183031 pmcid:PMC6512039 fatcat:upjfeh67izdkpp7ji5fpatblcm

Machine Learning in Multimodal Medical Imaging

Yong Xia, Zexuan Ji, Andrey Krylov, Hang Chang, Weidong Cai
2017 BioMed Research International  
Acknowledgments We would like to express our appreciation to all the authors for their informative contributions and the reviewers for their scientific contribution and support in making this special issue  ...  The papers in this special issue provide a useful message of machine learning techniques in dealing with multimodal medical images.  ...  This special issue illustrates the important role that machine learning techniques play in the multimodal medical imaging fields.  ... 
doi:10.1155/2017/1278329 pmid:28357398 pmcid:PMC5357511 fatcat:w43l56sbl5b5xbgvizulf5oh5q

Machine Learning for Medical Applications

Huiyu Zhou, Jinshan Tang, Huiru Zheng
2015 The Scientific World Journal  
In this special issue, we provide a forum to present the cutting-edge machine learning techniques in medical applications, including the learning of similarities across different image modalities, organ  ...  Machine learning (ML) has been well recognized as an effective tool for researchers to handle the problems in signal and image processing.  ...  Acknowledgments The guest editors would like to thank all the authors for submitting their high quality manuscripts to this special issue and all the reviewers for providing quality and timely reviews.  ... 
doi:10.1155/2015/825267 pmid:25692180 pmcid:PMC4321677 fatcat:4nwpcxly7bfszpu62jmjz4s42a

Machine Learning: Discovering the Future of Medical Imaging

Bradley J. Erickson
2017 Journal of digital imaging  
This issue is devoted to reports on the application of machine learning in medical imaging, some of which were presented at the inaugural Conference on Machine Intelligence in Medical Imaging (C-MIMI).  ...  BThe measure of a superhero is always his nemesis^- David Lyons This special issue demonstrates the incredible potential of machine learning to advance medical imaging science, and the attention to methods  ... 
doi:10.1007/s10278-017-9994-1 pmid:28653122 pmcid:PMC5537101 fatcat:q3mhu7vlgrgybpfgzlovlbm4wa

Guest editorial of the IJCARS—BVM 2018 special issue

Andreas Maier, Thomas M. Deserno, Heinz Handels, Klaus Maier-Hein, Christoph Palm, Thomas Tolxdorff
2019 International Journal of Computer Assisted Radiology and Surgery  
It is a great pleasure to present this special issue in the International Journal of Computer Assisted Radiology and Surgery on the German workshop on medical image computing "Bildverarbeitung für die  ...  Five out of these six papers address topics of machine or deep learning in medical imaging which is in line with the growing importance of machine learning and pattern recognition in our field.  ... 
doi:10.1007/s11548-018-01902-0 fatcat:xhy2qjixpbfjzhbbe2jzhvqkxu

Introduction to the Special Issue on Computational Intelligence for Biomedical Data and Imaging

M. Tanveer, P. Khanna, M. Prasad, C. T. Lin
2020 ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)  
Computational intelligence in the field of biomedical data includes working in the field of image processing, computer vision, machine learning, deep learning, big data analytics, and cloud computing.  ...  Data acquisition is a major issue in the field of biomedical analysis due to problems in collaboration between medical experts and researchers.  ...  The subsequent articles in this special issue focus on the application of novel machine learningbased algorithms for biomedical applications.  ... 
doi:10.1145/3381919 fatcat:taaidy72hzaxjcmrozp6qmmbt4

Machine Learning in Image Processing

Olivier Lézoray, Christophe Charrier, Hubert Cardot, Sébastien Lefèvre
2008 EURASIP Journal on Advances in Signal Processing  
QUICK FACTS ABOUT THE SPECIAL ISSUE The guest editors suggested putting together this special issue on machine learning in image processing to the editor-inchief in November 2006.  ...  SCANNING THE SPECIAL ISSUE This special issue attempts to provide a comprehensive overview of the most recent trends in machine learning in image processing.  ... 
doi:10.1155/2008/927950 fatcat:5yq3erodcvdt5idczn5xdpodbi

Multimedia analysis for medical applications

Jun Zhang, Mingxia Liu, Yi Zhen
2019 Multimedia Systems  
This special issue serves as a forum for researchers all over the world to discuss their research work and recent advances in multimedia learning methods for various medical applications, including medical  ...  Many machine learning, signal/image processing, and data mining algorithms have been successfully developed for multimedia analysis.  ...  This special issue serves as a forum for researchers all over the world to discuss their research work and recent advances in multimedia learning methods for various medical applications, including medical  ... 
doi:10.1007/s00530-019-00609-9 fatcat:apbpvlme3jeinb43scybnn2ka4

The role of machine and deep learning in modern medical physics

Issam El Naqa, Shiva Das
2020 Medical Physics (Lancaster)  
Quantitative image analysis, also known as radiomics, has been an active area of research in medical imaging. In "Machine and Deep Learning Methods for Radiomics," Avanzo et al.  ...  It is our hope that this special issue will serve as a practical guide for medical physicists interested in deploying machine/deep learning technologies in medicine, radiology, or radiation oncology and  ... 
doi:10.1002/mp.14088 pmid:32418342 fatcat:fgbfduqn4jbtjmh6csr4aar3la

Artificial Intelligence in Medical Applications

Yung-Kuan Chan, Yung-Fu Chen, Tuan Pham, Weide Chang, Ming-Yuan Hsieh
2018 Journal of Healthcare Engineering  
artificial intelligence, expert systems, data mining, machine learning, and image processing which could be built on top of them. is special issue summarizes the most recent developments in the field,  ...  (v) Medical Signal and Image Processing Techniques irty-three papers were submitted for this special issue.  ...  artificial intelligence, expert systems, data mining, machine learning, and image processing which could be built on top of them. is special issue summarizes the most recent developments in the field,  ... 
doi:10.1155/2018/4827875 pmid:30123442 pmcid:PMC6079562 fatcat:ditffnlgz5fcnoen6ukgfjvhta

Machine Learning Methods with Noisy, Incomplete or Small Datasets

Cesar F. Caiafa, Zhe Sun, Toshihisa Tanaka, Pere Marti-Puig, Jordi Solé-Casals
2021 Applied Sciences  
In this article, we present a collection of fifteen novel contributions on machine learning methods with low-quality or imperfect datasets, which were accepted for publication in the special issue "Machine  ...  We believe that this special issue will bring new ideas for solving this challenging problem, and will provide clear examples of application in real-world scenarios.  ...  The aim of this Special Issue was to collect novel contributions on machine learning methods for low-quality datasets, to contribute to the dissemination of new ideas to solve this challenging problem,  ... 
doi:10.3390/app11094132 doaj:b756026d4f1b45e89f158fe4378f7e8c fatcat:zpqxuxf5ora2xk3zpmge73tyl4
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