{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,30]],"date-time":"2026-03-30T21:45:55Z","timestamp":1774907155355,"version":"3.50.1"},"reference-count":38,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2019,1,15]],"date-time":"2019-01-15T00:00:00Z","timestamp":1547510400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100005416","name":"Norges Forskningsr\u00e5d","doi-asserted-by":"publisher","award":["247689"],"award-info":[{"award-number":["247689"]}],"id":[{"id":"10.13039\/501100005416","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Imaging"],"abstract":"<jats:p>Noise-based quality evaluation of MRI images is highly desired in noise-dominant environments. Current noise-based MRI quality evaluation methods have drawbacks which limit their effective performance. Traditional full-reference methods such as SNR and most of the model-based techniques cannot provide perceptual quality metrics required for accurate diagnosis, treatment and monitoring of diseases. Although techniques based on the Moran coefficients are perceptual quality metrics, they are full-reference methods and will be ineffective in applications where the reference image is not available. Furthermore, the predicted quality scores are difficult to interpret because their quality indices are not standardized. In this paper, we propose a new no-reference perceptual quality evaluation method for grayscale images such as MRI images. Our approach is formulated to mimic how humans perceive an image. It transforms noise level into a standardized perceptual quality score. Global Moran statistics is combined with local indicators of spatial autocorrelation in the form of local Moran statistics. Quality score is predicted from perceptually weighted combination of clustered and random pixels. Performance evaluation, comparative performance evaluation and validation by human observers, shows that the proposed method will be a useful tool in the evaluation of retrospectively acquired MRI images and the evaluation of noise reduction algorithms.<\/jats:p>","DOI":"10.3390\/jimaging5010020","type":"journal-article","created":{"date-parts":[[2019,1,16]],"date-time":"2019-01-16T03:09:13Z","timestamp":1547608153000},"page":"20","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Local Indicators of Spatial Autocorrelation (LISA): Application to Blind Noise-Based Perceptual Quality Metric Index for Magnetic Resonance Images"],"prefix":"10.3390","volume":"5","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4681-2958","authenticated-orcid":false,"given":"Michael","family":"Osadebey","sequence":"first","affiliation":[{"name":"Department of Computer Science, Norwegian University of Science and Technology, Teknologivegen 22, N-2815 Gj\u00f8vik, Norway"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marius","family":"Pedersen","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Norwegian University of Science and Technology, Teknologivegen 22, N-2815 Gj\u00f8vik, Norway"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Douglas","family":"Arnold","sequence":"additional","affiliation":[{"name":"Montreal Neurological Institute and Hospital, McGill University, 3801 University St, Montreal, QC H3A 2B4, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Katrina","family":"Wendel-Mitoraj","sequence":"additional","affiliation":[{"name":"BrainCare Oy, Finn-Medi 1, PL 2000, 33521 Tampere, Finland"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,1,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Mandi\u0107, I., Pei\u0107, H., Lerga, J., and \u0160tajduhar, I. (2018). Denoising of x-ray images using the adaptive algorithm based on the LPA-RICI algorithm. J. Imaging, 4.","DOI":"10.3390\/jimaging4020034"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1016\/j.neuroimage.2005.01.007","article-title":"Comparison of physiological noise at 1.5 T, 3 T and 7 T and optimization of fMRI acquisition parameters","volume":"26","author":"Triantafyllou","year":"2005","journal-title":"Neuroimage"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"184","DOI":"10.1016\/j.media.2014.11.005","article-title":"Spatially variant noise estimation in MRI: A homomorphic approach","volume":"20","author":"Pie","year":"2015","journal-title":"Med. Image Anal."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1016\/j.mri.2013.12.001","article-title":"Noise estimation in parallel MRI: GRAPPA and SENSE","volume":"32","year":"2014","journal-title":"Magn. Reson. Imaging"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"483","DOI":"10.1016\/j.media.2010.03.001","article-title":"Robust Rician noise estimation for MR images","volume":"14","author":"Gedamu","year":"2010","journal-title":"Med. Image Anal."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1397","DOI":"10.1016\/j.mri.2009.05.025","article-title":"Noise estimation in single-and multiple-coil magnetic resonance data based on statistical models","volume":"27","year":"2009","journal-title":"Magn. Reson. Imaging"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1016\/S0730-725X(97)00199-9","article-title":"Estimation of the noise in magnitude MR images","volume":"16","author":"Sijbers","year":"1998","journal-title":"Magn. Reson. Imaging"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1335","DOI":"10.1088\/0031-9155\/52\/5\/009","article-title":"Automatic estimation of the noise variance from the histogram of a magnetic resonance image","volume":"52","author":"Sijbers","year":"2007","journal-title":"Phys. Med. Biol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"304","DOI":"10.1002\/ima.22065","article-title":"The clique potential of Markov random field in a random experiment for estimation of noise levels in 2D brain MRI","volume":"23","author":"Osadebey","year":"2013","journal-title":"Int. J. Imaging Syst. Technol."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"76","DOI":"10.1016\/j.media.2014.10.008","article-title":"Local estimation of the noise level in MRI using structural adaptation","volume":"20","author":"Tabelow","year":"2015","journal-title":"Med. Image Anal."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"357","DOI":"10.1088\/0031-9155\/37\/2\/004","article-title":"Assessment of noise in a digital image using the join-count statistic and the Moran test","volume":"37","author":"Chuang","year":"1992","journal-title":"Phys. Med. Biol."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"131","DOI":"10.1088\/0031-9155\/48\/8\/402","article-title":"A novel image quality index using Moran I statistics","volume":"48","author":"Chen","year":"2003","journal-title":"Phys. Med. Biol."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1007\/s10278-007-9013-z","article-title":"Quality of compressed medical images","volume":"20","author":"Shiao","year":"2007","journal-title":"J. Digit. Imaging"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"118","DOI":"10.1007\/s10278-005-8736-y","article-title":"A blurring index for medical images","volume":"19","author":"Chen","year":"2006","journal-title":"J. Digit. Imaging"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"210","DOI":"10.1007\/s10278-003-1652-0","article-title":"Quality degradation in lossy wavelet image compression","volume":"16","author":"Chen","year":"2003","journal-title":"J. Digit. Imaging"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"74","DOI":"10.1016\/j.mri.2017.07.016","article-title":"Modified-BRISQUE as no reference image quality assessment for structural MR images","volume":"43","author":"Chow","year":"2017","journal-title":"Magn. Reson. Imaging"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"4695","DOI":"10.1109\/TIP.2012.2214050","article-title":"No-reference image quality assessment in the spatial domain","volume":"21","author":"Mittal","year":"2012","journal-title":"IEEE Trans. Image Process."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1247","DOI":"10.5194\/gmd-7-1247-2014","article-title":"Root mean square error (RMSE) or mean absolute error (MAE)?\u2014Arguments against avoiding rmse in the literature","volume":"7","author":"Chai","year":"2014","journal-title":"Geosci. Model Dev."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"749","DOI":"10.1016\/j.atmosenv.2008.10.005","article-title":"Ambiguities inherent in sums-of-squares-based error statistics","volume":"43","author":"Willmott","year":"2009","journal-title":"Atmos. Environ."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"79","DOI":"10.3354\/cr030079","article-title":"Advantages of the mean absolute error (MAE) over the root mean square error (RMSE) in assessing average model performance","volume":"30","author":"Willmott","year":"2005","journal-title":"Clim. Res."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Kupinski, M.A., and Clarkson, E. (2005). Objective assessment of image quality. Small-Animal Spect Imaging, Springer Science & Business Media.","DOI":"10.1007\/0-387-25294-0_5"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1016\/j.bspc.2016.02.006","article-title":"Review of medical image quality assessment","volume":"27","author":"Chow","year":"2016","journal-title":"Biomed. Signal Process. Control"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Pieciak, T., Vegas-S\u00e1nchez-Ferrero, G., and Aja-Fern\u00e1ndez, S. (2016, January 13\u201316). Variance stabilization of noncentral-chi data: Application to noise estimation in MRI. Proceedings of the 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI), Prague, Czech Republic.","DOI":"10.1109\/ISBI.2016.7493523"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1016\/j.media.2015.01.004","article-title":"MRI noise estimation and denoising using non-local PCA","volume":"22","author":"Buades","year":"2015","journal-title":"Med. Image Anal."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1002\/sca.21179","article-title":"The contrast-to-noise ratio for image quality evaluation in scanning electron microscopy","volume":"37","author":"Timischl","year":"2015","journal-title":"Scanning"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1111\/j.2517-6161.1948.tb00012.x","article-title":"The interpretation of statistical maps","volume":"10","author":"Moran","year":"1948","journal-title":"J. R. Stat. Soc. Ser. B (Methodol.)"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"115","DOI":"10.2307\/2986645","article-title":"The contiguity ratio and statistical mapping","volume":"5","author":"Geary","year":"1954","journal-title":"Incorporated Statist."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1111\/j.1538-4632.1992.tb00261.x","article-title":"The analysis of spatial association by use of distance statistics","volume":"24","author":"Getis","year":"1992","journal-title":"Geogr. Anal."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"011016","DOI":"10.1117\/1.3277145","article-title":"Attributes of image quality for color prints","volume":"19","author":"Pedersen","year":"2010","journal-title":"J. Electron. Imaging"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Kim, H., Cho, K., Kim, J., Jin, K., and Kim, S. (2017). Robust parameter design of derivative optimization methods for image acquisition using a color mixer. J. Imaging, 3.","DOI":"10.3390\/jimaging3030031"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Singh, P., Mukundan, R., and De Ryke, R. (2017). Texture based quality analysis of simulated synthetic ultrasound images using local binary patterns. J. Imaging, 4.","DOI":"10.20944\/preprints201710.0181.v1"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"335","DOI":"10.1016\/j.media.2007.12.003","article-title":"Efficient and generalizable statistical models of shape and appearance for analysis of cardiac MRI","volume":"12","author":"Andreopoulos","year":"2008","journal-title":"Med. Image Anal."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1045","DOI":"10.1007\/s10278-013-9622-7","article-title":"The cancer imaging archive (TCIA): Maintaining and operating a public information repository","volume":"26","author":"Clark","year":"2013","journal-title":"J. Digit. Imaging"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"463","DOI":"10.1109\/42.712135","article-title":"Design and construction of a realistic digital brain phantom","volume":"17","author":"Collins","year":"1998","journal-title":"IEEE Trans. Med. Imaging"},{"key":"ref_35","unstructured":"Tomasi, C., and Manduchi, R. (1998, January 7). Bilateral filtering for gray and color images. Proceedings of the Sixth International Conference On Computer Vision, Bombay, India."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Van Ngo, K., Storvik, J.J., Dokkeberg, C.A., Farup, I., and Pedersen, M. (2015). QuickEval: A web application for psychometric scaling experiments. SPIE\/IS&T Electronic Imaging, International Society for Optics and Photonics.","DOI":"10.1117\/12.2077548"},{"key":"ref_37","unstructured":"Corder, G.W., and Foreman, D.I. (2014). Nonparametric Statistics: A Step-by-Step Approach, John Wiley & Sons."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"684","DOI":"10.1109\/TIP.2013.2293423","article-title":"Gradient magnitude similarity deviation: A highly efficient perceptual image quality index","volume":"23","author":"Xue","year":"2014","journal-title":"IEEE Trans. Image Process."}],"container-title":["Journal of Imaging"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2313-433X\/5\/1\/20\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T12:26:12Z","timestamp":1760185572000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2313-433X\/5\/1\/20"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,1,15]]},"references-count":38,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2019,1]]}},"alternative-id":["jimaging5010020"],"URL":"https:\/\/doi.org\/10.3390\/jimaging5010020","relation":{},"ISSN":["2313-433X"],"issn-type":[{"value":"2313-433X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,1,15]]}}}