000			01528nam a22001697a 4500
003			NUST
082			_a629.8
100			_a Munir, Zonaira _9119690
245			_aDiagnosing and localizing Covid-19 in High resolution CT(HRCT) scans using Deep learning / _cZonaira Munir
264			_aIslamabad : _bSMME- NUST; _c2023.
300			_a62p. ; _bSoft Copy _c30cm.
520			_aWith the break-out of covid-19 as a world-wide pandemic that has a higher spread rate, it became a need to find a solution that would work in the favor of the patient as well as the radiologist. Since 2020, there have been many attempts to cater for the problem. Many researchers proposed detection and classification models in an attempt to automate some parts of the diagnostics process. The common methods found in the reported literature includes using models like VGG16, FCNN, Unet, ResUnet, Inception net and Alex net for the tasks of detection and classification of covid-19 benign or malignant. This thesis aims to explore the possibility of detecting and localizing covid-19. The covid lesions were segmented and then detected using Attention Res-Unet. The lungs were segmented into the major lobes using Unet and then an attempt was made to localize the detected lesions with respect to segmented Lung Lobes.
650			_aMS Robotics and Intelligent Machine Engineering _9119486
700			_aSupervisor : Dr. Muhammad jawad khan _9119689
856			_uhttp://10.250.8.41:8080/xmlui/handle/123456789/34963
942			_2ddc _cTHE
999			_c607320 _d607320