Munir, Zonaira <br/><br/>
Diagnosing and localizing Covid-19 in High resolution CT(HRCT) scans using Deep learning / 
Zonaira Munir 
 - 62p. ;  Soft Copy  30cm. 
<br/><br/> With the break-out of covid-19 as a world-wide pandemic that has a higher spread rate,<br/>it became a need to find a solution that would work in the favor of the patient as well<br/>as the radiologist. Since 2020, there have been many attempts to cater for the problem.<br/>Many researchers proposed detection and classification models in an attempt to<br/>automate some parts of the diagnostics process.<br/>The common methods found in the reported literature includes using models like<br/>VGG16, FCNN, Unet, ResUnet, Inception net and Alex net for the tasks of detection<br/>and classification of covid-19 benign or malignant.<br/>This thesis aims to explore the possibility of detecting and localizing covid-19. The<br/>covid lesions were segmented and then detected using Attention Res-Unet. The lungs<br/>were segmented into the major lobes using Unet and then an attempt was made to<br/>localize the detected lesions with respect to segmented Lung Lobes.  
<br/><br/><label>Subjects--Topical Terms: </label><br/>MS Robotics and Intelligent Machine Engineering    
<br/><br/><label>Dewey Class. No.: </label>629.8