Patent ID: 11967079
Assignee: QURE.AI TECHNOLOGIES PRIVATE LIMITED
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. A system (100) for detecting Large Vessel Occlusion (LVO) on a Computational Tomography Angiogram (CTA) automatically, wherein the system (100) comprises:
a memory and at least one processor, wherein the processor comprises:
a vascular territory segmentation module configured to:
receive a set of CTA images, wherein each CTA image is a slice of a region of interest (ROI) comprising a bone region and an intracranial volume (ICV) region; and
mark a territory of vascular segments in the ICV region for each slice of the ROI;

an ICV segmentation module configured to process each slice of the ROI by:
removing bones and noise due to veins/capillaries from each slice of the ROI based on the marked territory of the ICV region using a semantic-segmentation based deep learning approach;
upon removal of the bones, applying a Maximum Intensity Projection (MIP) on each slice of the ROI;
combining the processed slices of the ROI to develop a CTA image;
segmenting the developed CTA image into a Middle Cerebral Artery (MCA) region and an Internal Cerebral Artery (ICA) region based on the marked territory of the ICV; and
sending the segmented MCA region and ICA region to a MCA-LVO classifier and an ICA-LVO classifier respectively;
wherein the MCA-LVO classifier is configured to determine presence of the LVO on the received MCA region using deep learning techniques;
wherein the ICA-LVO classifier is configured to determine presence of the LVO on the received ICA region using the deep learning techniques; and
report the presence of the LVO on the segmented MCA and ICA regions to a user based on the determination by the respective MCA-LVO classifier and ICA-LVO classifier.