A malignant cell is an abnormal and aggressive cell that can invade nearby tissues and spread to other parts of the body, leading to cancer. Surgical image analysis plays a pivotal role in modern healthcare by enhancing the precision and safety of surgical procedures. Detecting malignant cells is crucial for early diagnosis and treatment of cancer. Timely detection allows for effective intervention, better treatment outcomes, and improved chances of successful recovery. It helps prevent the spread of cancer, enables appropriate medical decisions, and enhances the potential for less invasive treatment options. This paper aims to address the application of deep learning techniques for surgical image detection and localization. The primary objective is to automatically identify and precisely locate critical anatomical structures, anomalies, or pathological entities within surgical images, including X-rays, MRIs, and endoscopic visuals.