Zagazig University Digital Repository
Home
Thesis & Publications
All Contents
Publications
Thesis
Graduation Projects
Research Area
Research Area Reports
Search by Research Area
Universities Thesis
ACADEMIC Links
ACADEMIC RESEARCH
Zagazig University Authors
Africa Research Statistics
Google Scholar
Research Gate
Researcher ID
CrossRef
COVID-19 diagnosis from CT scans and chest X-ray images using low-cost Raspberry Pi
Faculty
Computer Science
Year:
2021
Type of Publication:
ZU Hosted
Pages:
Authors:
Khalied Mohamed Hosny
Staff Zu Site
Abstract In Staff Site
Journal:
Plos one Plos
Volume:
2021
Keywords :
COVID-19 diagnosis from , scans , chest X-ray
Abstract:
The diagnosis of COVID-19 is of vital demand. Several studies have been conducted to decide whether the chest X-ray and computed tomography (CT) scans of patients indicate COVID-19. While these efforts resulted in successful classification systems, the design of a portable and cost-effective COVID-19 diagnosis system has not been addressed yet. The memory requirements of the current state-of-the-art COVID-19 diagnosis systems are not suitable for embedded systems due to the required large memory size of these systems (e.g., hundreds of megabytes). Thus, the current work is motivated to design a similar system with minimal memory requirements. In this paper, we propose a diagnosis system using a Raspberry Pi Linux embedded system. First, local features are extracted using local binary pattern (LBP) algorithm. Second, the global features are extracted from the chest X-ray or CT scans using multi-channel fractional-order Legendre-Fourier moments (MFrLFMs). Finally, the most significant features (local and global) are selected. The proposed system steps are integrated to fit the low computational and memory capacities of the embedded system. The proposed method has the smallest computational and memory resources, less than the state-of-the-art methods by two to three orders of magnitude, among existing state-of-the-art deep learning (DL)-based methods.
Author Related Publications
Khalied Mohamed Hosny, "SEMANTIC REPRESENTATION OF MUSIC DATABASE USING NEW ONTOLOGY-BASED SYSTEM", Journal of Theoretical and Applied Information Technology, 2020
More
Khalied Mohamed Hosny, "Building a New Semantic Social Network Using Semantic Web-Based Techniques", ِASPG, 2021
More
Khalied Mohamed Hosny, "New Graphical Ultimate Processor for Mapping Relational Database to Resource Description Framework", IEEE, 2022
More
Khalied Mohamed Hosny, "Fast computation of accurate Zernike moments", Springer, 2008
More
Khalied Mohamed Hosny, "Accurate Computation of QPCET for Color Images in Different Coordinate Systems", SPIE, 2017
More
Department Related Publications
Abdul Wahid Ibrahim Mahmoud Khamis, "Cameraphone Recognition of Arabic Fingerspelling", International Journal of Computer Science and Information Technology & Security (IJCSITS), 2013
More
Mohammed Abdel Basset Metwally Attia, "A hybrid flower pollination algorithm for solving ill-conditioned set of equations", Int. J. Bio-Inspired Computation, 2016
More
Zaher Awad Aboelenieen Elhendy, "NEW APPROACH TO IMAGE EDGE DETECTION BASED ON QUANTUM ENTROPY", JOURNAL OF RUSSIAN LASER RESEARCH, 2016
More
Doaa El-Shahat Barakat Mohammed, "A hybrid whale optimization algorithm based on local search strategy for the permutation flow shop scheduling problem", North-Holland, 2018
More
Ibrahiem Mahmoud Mohamed Elhenawy, "A hybrid whale optimization algorithm based on local search strategy for the permutation flow shop scheduling problem", North-Holland, 2018
More
جامعة المنصورة
جامعة الاسكندرية
جامعة القاهرة
جامعة سوهاج
جامعة الفيوم
جامعة بنها
جامعة دمياط
جامعة بورسعيد
جامعة حلوان
جامعة السويس
شراقوة
جامعة المنيا
جامعة دمنهور
جامعة المنوفية
جامعة أسوان
جامعة جنوب الوادى
جامعة قناة السويس
جامعة عين شمس
جامعة أسيوط
جامعة كفر الشيخ
جامعة السادات
جامعة طنطا
جامعة بنى سويف