Ovarian cancer is a challenging disease to detect and diagnose, especially in complex medical images where the cancerous lesions may be small and difficult to differentiate from surrounding healthy tissue. The use of deep learning algorithms has shown promising results in computer-aided diagnosis of various cancers. This study aims to develop a smart detection system for ovarian cancer in complex medical images using deep learning techniques. The proposed system will have the ability to accurately and efficiently identify cancerous lesions, leading to earlier detection and improved treatment outcomes. Through the use of advanced computer vision and machine learning methods, the system will be able to learn from a large dataset of medical images and make accurate predictions. This research has the potential to significantly improve the diagnosis and treatment of ovarian cancer, ultimately saving lives.