A Two-Stage Method for Diagnosing COVID-19, Leveraging CNN, and Transfer Learning on CT Scan Images
Lung infection represents one of the most perilous indicators of Covid-19. The most efficient diagnostic approach entails the analysis of CT scan images. Utilizing deep learning algorithms and machine vision, computer scientists have devised a method for automated detection of this disease. This stu...
Saved in:
| Main Authors: | Touba torabipour, Abolfazl Gandomi, Mohammad Ghanimi |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
University of science and culture
2023-07-01
|
| Series: | International Journal of Web Research |
| Subjects: | |
| Online Access: | https://ijwr.usc.ac.ir/article_197180_ca24efdc59c110e9cfdd5830269b4608.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
ROLE OF RADIOGRAPHER IN HANDLING COVID-19 AT CT SCAN ROOM DURING PANDEMIC
by: Aisyatun Mardliyyah, et al.
Published: (2020-11-01) -
Integrated ensemble CNN and explainable AI for COVID-19 diagnosis from CT scan and X-ray images
by: Reenu Rajpoot, et al.
Published: (2024-10-01) -
Role of USG and CT scan in evaluating ovarian lesions
by: Mayur Khandhedia, et al.
Published: (2017-01-01) -
AI-Powered Lung Cancer Detection: Assessing VGG16 and CNN Architectures for CT Scan Image Classification
by: Rapeepat Klangbunrueang, et al.
Published: (2025-02-01) -
A Two-Stage U-Net Framework for Interactive Segmentation of Lung Nodules in CT Scans
by: Luis Fernandes, et al.
Published: (2025-01-01)