System and method for automatically detecting large vessel occlusion on a computational tomography angiogram

The present subject matter discloses a system and method for detecting Large Vessel Occlusion (LVO) on a Computational Tomography Angiogram (CTA) automatically. the system comprises a vascular-territory-segmentation module, an ICV segmentation module, MCA-LVO classifier and ICA-LVO classifier. The vascular territory segmentation module is configured to receive a set of CTA images and to mark a territory of vascular segments in the ICV region for each slice of the ROI. The ICV segmentation module is configured to process each slice of the ROI. The processed slices of the ROI are combined to develop a CTA image after application of MIP and the developed CTA image is segmented into a Middle Cerebral Artery (MCA) region and an Internal Cerebral Artery (ICA) region. The MCA-LVO and ICA-LVO classifiers determine presence of the LVO on the received MCA and ICA region using Deep Learning techniques and accordingly the presence of the LVO is reported.