Hybrid Approach for Lossless MRI DICOM Image Compression

Abstract

In the modern medical world, technology has renewed the ways healthcare specialists detect and handling patients.  The medical devices are responsible for image acquisition and store the images in standardized format. Medical professional need to store the huge number of images about patients for monitoring and diagnose the disease. It leads to requirement of huge memory space and also requires high bandwidth to transfer the image. Image compression necessary to decrease the memory size and increase the transmission speed with standard bandwidth. The former research presented a lossless technique that compress the image without affect the quality of the image using Huffman coding. This technique maintains the quality of the image when reconstruct the image. The second technique is based on bit level compression. The highest bit levels are compressed using LZW(Lempel–Ziv–Welch) methods. Remaining levels are compressed using JPEG compression method. In the Huffman coding compression is achieved depends on the redundancy in the data. LZW became more complex when dealing with larger dataset. To reduce this problem and to achieve the higher compression ratio and reduce the memory size of the image the new hybridization method is proposed. The proposed method hybrid the LZW and Huffman coding to achieve the highest compression ratio than prior technique. In this research, DICOM MRI images are pre-processed using Ant Colony Optimization (ACO) technique. The pre-processed image is transformed by means of Lempel–Ziv–Welch (LZW) and then apply Huffman coding to encode the image. And decompression process is done by applying Huffman decoding and then inverse LZW inverse transform. The presented method prove that attains greater performance than the former method.