Authors: T.P. Byjubai; Elizabeth Elias
Addresses: Department of Electronics and Communication Engineering, National Institute of Technology, NIT Campus P.O., Calicut-673 601 Kerala, India. ' Department of Electronics and Communication Engineering, National Institute of Technology, NIT Campus P.O., Calicut-673 601 Kerala, India
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.
Keywords: compressed sensing; DICOM standard; DICOM image reconstruction; sparse transforms; objective image quality; quality measurement; multi-scale transforms; medical imaging; image compression; medical images; quality assessement.
International Journal of Medical Engineering and Informatics, 2012 Vol.4 No.3, pp.262 - 273
Received: 08 May 2021
Accepted: 12 May 2021
Published online: 02 Aug 2012 *