<scp>FFCAEs</scp> : An efficient feature fusion framework using cascaded autoencoders for the identification of gliomas-Reference-Cited by-同舟云学术

FFCAEs : An efficient feature fusion framework using cascaded autoencoders for the identification of gliomas

Published:2022-10-21 Issue:2 Volume:33 Page:483-494
ISSN:0899-9457
Container-title:International Journal of Imaging Systems and Technology
language:en
Short-container-title:Int J Imaging Syst Tech

Author:

Gudigar Anjan¹^ORCID,Raghavendra U.¹^ORCID,Rao Tejaswi N.¹,Samanth Jyothi²,Rajinikanth Venkatesan³^ORCID,Satapathy Suresh Chandra⁴,Ciaccio Edward J.⁵,Wai Yee Chan⁶,Acharya U. Rajendra⁷⁸⁹

Affiliation:

1. Department of Instrumentation and Control Engineering, Manipal Institute of Technology Manipal Academy of Higher Education Manipal India

2. Department of Cardiovascular Technology, Manipal College of Health Professions Manipal Academy of higher education Manipal India

3. Department of Computer Science and Engineering, Division of Research and Innovation Saveetha School of Engineering, SIMATS Chennai Tamil Nadu India

4. School of Computer Engineering Kalinga Institute of Industrial Technology Bhubaneswar India

5. Department of Medicine Columbia University Medical Center New York New York USA

6. Gleneagles Hospital Kuala Lumpur Department of Radiology, Jln Ampang Kuala Lumpur Malaysia

7. School of Mathematics, Physics and Computing University of Southern Queensland Springfield Australia

8. Department of Biomedical Informatics and Medical Engineering Asia University Taichung Taiwan

9. International Research Organization for Advanced Science and Technology (IROAST) Kumamoto University Kumamoto Japan

Publisher

Wiley

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Software,Electronic, Optical and Magnetic Materials

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/ima.22820

Reference40 articles.

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2. The 2007 WHO Classification of Tumours of the Central Nervous System

3. The 2016 World Health Organization Classification of Tumors of the Central Nervous System: a summary

4. Assessment of the pathological grade of astrocytic gliomas using an MRI score

5. Supratentorial diffuse astrocytic tumours: proposal of an MRI classification

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