Rain Defect Detection application from CT images using YOLOv8

Abstract

"The study forwards a computer-aided detection application and a deep learning algorithm for detecting brain defects from CT images, which pave a path to improve the accuracy of the CT image interpretation task considering both the sensitivity and the specificity of the diagnosis of the defect. The application ensures a more accurate diagnosis and interface, which is easy to use for medical professionals. The proposed system leverages YOLOv8, a deep learning algorithm utilised specially for real-time object detection. The method for detecting brain defects is used in clinical settings and smoothly incorporated into the current processes of medical imaging. The study demonstrates the viability and efficacy of employing YOLOv8 for automated brain defect diagnosis from CT scans, opening the door for improvements in patient outcomes and medical imaging technology breakthroughs."