Optimization and Performance Analysis of the SIREN Algorithm for Lossless Image Compression Across Various Medical Imaging Modalities

Modern healthcare depends significantly on medical imaging technology which enables both patient diagnosis and medical treatment development and research activities. Efficient storage and transmission methods for high-resolution medical images have become essential because their increasing volume needs to be managed but image quality must remain unaffected. Lossless image compression techniques maintain complete original image integrity which makes them usable for medical clinical purposes. The research examines the optimization of SIREN (Sinusoidal Representation Networks) algorithm for lossless image compression systems across X-rays and MRIs and CT scans and ultrasound images.The suggested method implements SIREN because this algorithm adopts sinusoidal activation functions to deliver precise high-frequency image modeling capabilities. The evaluation determines compression ratio and processing speed as well as reconstruction accuracy for SIREN while assessing performance versus established lossless compression techniques. Research outcomes show that by implementing SIREN algorithm with optimized features medical institutions can enjoy improved image quality and reduced storage needs. The research promotes medical data management systems development by enhancing transmission speed together with better access to medical images in healthcare settings.