Efficient anomaly detection from medical signals and images with convolutional neural networks for Internet of medical things (IoMT) systems-Reference-Cited by-同舟云学术

Efficient anomaly detection from medical signals and images with convolutional neural networks for Internet of medical things (IoMT) systems

Published:2021-12-18 Issue:1 Volume:38 Page:
ISSN:2040-7939
Container-title:International Journal for Numerical Methods in Biomedical Engineering
language:en
Short-container-title:Numer Methods Biomed Eng

Author:

Khalil Ali A.¹^ORCID,Ibrahim Fatma²,Abbass Mohamed Y.³,Haggag Nehad²,Mahrous Yasser²,Sedik Ahmed⁴,Elsherbeeny Zeinab²,Khalaf Ashraf A. M.¹^ORCID,Rihan Mohamad²⁵^ORCID,El‐Shafai Walid²,El‐Banby Ghada M.⁶,Soltan Eman²,Soliman Naglaa F.⁷,Algarni Abeer D.⁷,Al‐Hanafy Waleed²,El‐Fishawy Adel S.²,El‐Rabaie El‐Sayed M.²,Al‐Nuaimy Waleed⁸,Dessouky Moawad I.²,Saleeb Adel A.²,Messiha Nagy W.²,El‐Dokany Ibrahim M.²,El‐Bendary Mohsen A. M.⁹,Abd El‐Samie Fathi E.²

Affiliation:

1. Department of Electronics and Communications, Faculty of Engineering Minia University Minia Egypt

2. Department of Electronics and Electrical Communications Engineering, Faculty of Electronic Engineering Menoufia University Menouf Egypt

3. Engineering Department Nuclear Research Center, Atomic Energy Authority Cairo Egypt

4. Department of the Robotics and Intelligent Machines, Faculty of Artificial Intelligence Kafrelsheikh University Kafrelsheikh Egypt

5. University of Cassino and Southern Lazio Italy

6. Department of Industrial Electronics and Control Engineering Faculty of Electronic Engineering, Menoufia University Menouf Egypt

7. Department of Information Technology, College of Computer and Information Sciences Princess Nourah bint Abdulrahman University P.O. Box 84428 Riyadh 11671 Saudi Arabia

8. Department of Electrical Engineering and Electronics The University of Liverpool Liverpool UK

9. Department of Electronics Technology, Faculty of Technology and Education Helwan University Cairo Egypt

Publisher

Wiley

Subject

Applied Mathematics,Computational Theory and Mathematics,Molecular Biology,Modeling and Simulation,Biomedical Engineering,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cnm.3530

Reference41 articles.

1. Fractal dimension based corneal fungal diagnosis;Balasubramian M;Proc SPIE,2006

2. FabijanA.Corneal endothelium image segmentation using feedforward neural network: Proceedings of the Federated Conference on Computer Science and Information Systems; IEEE Cataloge Number 2017:629‐637.

3. BuchtCPer S Göran M. “Fully automated corneal endothelial morphometric of images captured by clinical specular microscopy”. Ophthalmic Technologies XIX. International Society for Optics and Photonics; 2009;7163:125‐136.

4. Mean curvature mapping for detection of corneal shape abnormality

5. GirishaV ChandraKV.Machine intelligence on confocal microscope for detection of endothelium layer of corneal disease: Proceedings of IJCTER; 2016:148‐211.

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