Medical images plays a vital role in the area of medicine. It is important to store the medical images for future reference. So, there is a need for compressing of medical images for storage and communication purpose. Over the last few decades, many image compression methods have been introduced. They gives high compression ratio with loss of quality of image. Medical imagesshould always be stored in lossless format.There are several lossless compression techniques using which, original images can be restored.The objective of image compression is to reduce the redundancy of the image and to store or transmit data in an efficient form.The different compression algorithms currently in use in medical imaging,One such type of image compression is Fractal Image Compression (FIC). These FIC techniques commonly uses the optimization techniques to find the optimal best solution. The aim of the FIC is to divide the image into pieces or sections and then finds self-similar ones. It produces high compression ratio, fast decompression in short amount of time. In this paper, Flower Pollination Based Optimization approach is used for fractal image compression. This optimization technique effectively reduces the encoding time while retaining the quality of the image.Here, Flower pollination algorithm(FPA) is compared with Genetic algorithm(GA)and their performances are analyzed in terms of compression ratio, encoding time and PSNR(Peak Signal-to Noise Ratio) value.