Magnetic Resonance Imaging (MRI) is a medical imaging technique which is most commonly used in radiology to visualize the internal structure and function of the body. MRI provides better contrast between the different soft tissues of the body than computed tomography (CT) does. This makes it especially useful in the brain and cancer imaging. An MRI scan can be used as an extremely accurate method of disease detection throughout the body. In the head, trauma to the brain can be seen as bleeding or swelling. Other abnormalities often found include brain aneurysms , stroke , tumors of the brain , as well as tumors or inflammation of the spine. Medical images such as MRI can be produced in three forms. A two-dimensional slice is a single snapshot of the tissue. Three-dimensional or structural MRI is a 3D sequence composed of 2D slices. Third form of MRI data is four-dimensional or functional MRI scans which are 3D scans over time. Hence, each functional MRI scan is composed of a number of 3D sequences. Large number of MRI images is routinely generated. For follow ups and further study, these images need to be stored which requires large amount of storage space. With tele-medicine becoming more popular, there is also a need for reduction in transmission time. Hence, compression of medical images plays an important role for efficient storage and transmission. Different methods for lossy compression of images and video sequences are available. The exact reconstruction of the images is not possible for the lossy compressed images. For medical diagnosis purposes lossy compression of images is not desired since it may lead to loss of critical clinical information and may cause misdiagnosis. In the lossless compression of volumetric medical images an important number of technical advances have been reported. Some of the existing works have assumed that all slices are independent and can be compressed separately. This means that no correlation among adjacent slices (inter-slice correlation) is exploited. It is shown that even for data sets with a small number of 2D slices and a high slice distance there is significant gain in compression ratio by compressing the 3D data compared to compressing the 2D slices Key Words MRI, 3D medical image, compression, block matching, context modeling
