An improved active contour medical image compression technique with lossless region of interest

Digital medical images like X-Ray, Magnetic Resonance Imaging (MRI), Ultrasound, Computed Tomography (CT) are extensively used in diagnosis. The ease of storing and transmission of digital medical images is a boon to patients and medical professionals. Due to the large volume of images, image compression is required to accomplish fast and efficient transmission and reduction in storage space of medical images. Compression techniques used are very important while compressing digital medical images as the region of interest for diagnosis is generally small when compared to the whole image captured. Lossless compression techniques compress with no data loss but have low compression rate and lossy compression techniques can compress at high compression ratio but with a slight loss of data. Using lossless techniques in medical image does not give enough advantage in transmission and storage and lossy techniques may lose crucial data required for diagnosis. To maximize compression, in this paper it is proposed to investigate multiple compression techniques based on Region of Interest (ROI). In this paper a novel active contour method is proposed which is adaptive and marks the ROI without edges. The marked area of ROI is compressed using lossless compression and the other areas of the image are compressed using lossy wavelet compression techniques. The proposed procedure when applied on diverse MRI images, achieved an overall compression ratio of 69-81% without loss in the originality of ROI.