Image quality assessment in medical imaging based on compressed sensing Online publication date: Mon, 11-Aug-2014
by T.P. Byjubai; Elizabeth Elias
International Journal of Medical Engineering and Informatics (IJMEI), Vol. 4, No. 3, 2012
Abstract: Compressed sensing (CS)-based compression and reconstruction of images is an upcoming area of research. In this paper, an efficient application of CS in medical imaging is proposed. The increasing volume of data generated by some medical imaging modalities necessitates different compression techniques for the reduction of storage space and transmission bandwidth. Digital imaging and communications in medicine (DICOM) standard is the backbone of modern medical image display and addresses the exchange of digital information between medical imaging equipment and other systems. When the compression and reconstruction of DICOM images are done using CS, it is found that the artefacts in the reconstructed images are strongly dependent on the sparsifying transforms used in CS. For evaluating the performance of various sparsifying transforms of CS, an objective image quality measurement analysis is conducted. From the experiments, it is found that multi-scale transforms outperform the conventional transforms.
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