Implementing Detection of Covid-19 USing Multimodal Imaging Data
Abstract & Details
Research Area
Computer Science
Keywords
Keywords: - COVID-19 Detection
Deep Learning
Convolutional Neural Network
Radiological Imaging
CT scan
Ultrasound.
Abstract
The COVID-19 pandemic has spread rapidly across the globe and has caused life threating consequences to mankind ever since it started from Wuhan, China in December 2019. Early Detection and Prevention can help in containing the spread of the disease. Screening of large number of people is pressing priority. One of the crucial steps towards achieving this goal is through radiological examination. The approach we followed aims to remove unwanted noise from images so that the deep learning models can focus on detection of disease. The results prove that Ultrasound imaging is far more superior than X-Ray and CT scan. In this study, we identify a suitable Convolutional Neural Network (CNN) model that will detect the Covid-19 Positive patients using chest X-Ray images. Images of Covid positive and negative patients are divided into trainable images and testing images. This test can be done on any computer and by any medical examiner or technician to detect COVID-19 in a matter of few seconds.
License
This work is licensed under a Creative
Commons
Attribution-ShareAlike 4.0 International License.
Author Information
| # | Name | Institute / Affiliation |
|---|---|---|
| 1 | Neha G | Dayanand Sagar Academy Of Technology And Management |
| 2 | Rhema Rakshita S | Dayanand Sagar Academy Of Technology And Management |
| 3 | Ayeesha Taneem | Dayanand Sagar Academy Of Technology And Management |
| 4 | Manasa Sandeep | Dayanand Sagar Academy Of Technology And Management |
How to Cite
Use the following formats to cite this article in your research.
APA Style
G, Neha, S, Rhema Rakshita, Taneem, Ayeesha, & Sandeep, Manasa (2021). Implementing Detection of Covid-19 USing Multimodal Imaging Data. International Journal of Advance Research and Innovative Ideas In Education, 7(4), 331-338.
MLA Style
G, Neha, et al. "Implementing Detection of Covid-19 USing Multimodal Imaging Data." International Journal of Advance Research and Innovative Ideas In Education, vol. 7, no. 4, 2021, pp. 331-338.
IEEE Style
Neha G, Rhema Rakshita S, Ayeesha Taneem, and Manasa Sandeep, "Implementing Detection of Covid-19 USing Multimodal Imaging Data," International Journal of Advance Research and Innovative Ideas In Education, vol. 7, no. 4, pp. 331-338, 2021.
Vancouver Style
G Neha, S Rhema Rakshita, Taneem Ayeesha, Sandeep Manasa. Implementing Detection of Covid-19 USing Multimodal Imaging Data. International Journal of Advance Research and Innovative Ideas In Education. 2021;7(4):331-338.
Harvard Style
G, Neha, S, Rhema Rakshita, Taneem, Ayeesha, & Sandeep, Manasa (2021) 'Implementing Detection of Covid-19 USing Multimodal Imaging Data', International Journal of Advance Research and Innovative Ideas In Education, 7(4), pp. 331-338.
Chicago Style
G, Neha, et al. "Implementing Detection of Covid-19 USing Multimodal Imaging Data." International Journal of Advance Research and Innovative Ideas In Education 7, no. 4 (2021): 331-338.
Turabian Style
G, Neha, et al. "Implementing Detection of Covid-19 USing Multimodal Imaging Data." International Journal of Advance Research and Innovative Ideas In Education 7, no. 4 (2021): 331-338.
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