A novel frequency-domain approach to the range migration algorithm for efficient medical image processing: Application in tumor detection and identification

This paper introduces a novel, computationally efficient range migration algorithm (RMA) specifically designed for medical microwave imaging applications. The proposed RMA achieves significant advancements over traditional methods, such as the Delay Multiply and Sum technique, by greatly reducing channel calculations and computational time while maintaining high image quality. The algorithm was validated using an antenna array system and a custom built phantom model. To further reduce noise and image artifacts after RMA application, Hamming, Gaussian, and Median filtering techniques were applied and compared. Notably, the Hamming filter significantly enhanced edge sharpness and improved tumor detection within human tissue compared to the other filters. A comprehensive complexity analysis was conducted to evaluate the algorithm’s efficiency and scalability, with a focus on computational time and resource utilization. Performance results offer valuable insights into the algorithm’s behavior across various operational conditions, Highlighting its potential to enhance healthcare diagnostics and improve patient outcomes, with promising prospects for future clinical adoption.