Wavelet-Based Lossy Compression Techniques For Medical Images

Abstract

Medical imaging is a powerful and useful tool for radiologists and consultants, allowing them to improve and facilitate their diagnosis. Worldwide, X-ray images represent 60% of the total amount of radiological images, the remaining consists of more newly developed image modalities such as Computed Tomography (CT), Magnetic Resonance Imaging (MRI), Ultrasound (US), Positron Emission Tomography (PET), Single Photon Emission Computerized Tomography (SPECT), Nuclear Medicine (NM), and Digital Subtraction Angiography (DSA). Image communication systems for medical images have bandwidth and image size constraints that result in time-consuming transmission of uncompressed raw image data. Thus image compression is a key factor to improve transmission speed and storage, but it risks losing relevant medical information. The radiology standard Digital Imaging and Communications in Medicine (DICOM3) provides rules for compression using lossless Joint Photographic Expert Group (JPEG) methods. However, at the moment there are no rules for acceptance of lossy compression in medical imaging and it is an extremely subjective decision. Acceptable levels of compression should never compromise diagnostic information. Wavelet technology has emerged as a promising compression tool to achieve a high compression ratio while maintaining an acceptable fidelity of image quality.