@inproceedings{a23b8afe4c154d369a63f7d2ec5d2f89,
title = "Image quality parameters in application of compressed sensing for MRI data",
abstract = "The acceleration of Magnetic Resonance Imaging techniques is still very important in current development. The application of Compressed Sensing for medical data accelerates the acquisition time and satisfies the image quality. The method relies on the sparsity condition and requires only the most important data instead of acquiring all data according to the Nyquist-Shannon sampling theorem. The paper shows the application of different image quality parameters in order to compare the original method of Compressed Sensing for phantom and medical data.",
author = "Micha{\l} Staniszewski",
note = "Publisher Copyright: {\textcopyright} 2018 Author(s).; International Conference of Numerical Analysis and Applied Mathematics, ICNAAM 2017 ; Conference date: 25-09-2017 Through 30-09-2017",
year = "2018",
month = jul,
day = "10",
doi = "10.1063/1.5043760",
language = "English",
series = "AIP Conference Proceedings",
publisher = "American Institute of Physics Inc.",
editor = "Charalambos Tsitouras and Theodore Simos and Theodore Simos and Theodore Simos and Theodore Simos and Theodore Simos",
booktitle = "International Conference of Numerical Analysis and Applied Mathematics, ICNAAM 2017",
address = "United States",
}