{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:12:07Z","timestamp":1760242327485,"version":"build-2065373602"},"reference-count":31,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2017,4,26]],"date-time":"2017-04-26T00:00:00Z","timestamp":1493164800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>In longitudinal medical studies, multicomponent images of the tissues, acquired at a given stage of a disease, are used to provide information on the fate of the tissues. We propose a quantification of the predictive value of multicomponent images using information theory. To this end, we revisit the predictive information introduced for monodimensional time series and extend it to multicomponent images. The interest of this theoretical approach is illustrated on multicomponent magnetic resonance images acquired on stroke patients at acute and late stages, for which we propose an original and realistic model of noise together with a spatial encoding for the images. We address therefrom very practical questions such as the impact of noise on the predictability, the optimal choice of an observation scale and the predictability gain brought by the addition of imaging components.<\/jats:p>","DOI":"10.3390\/e19050187","type":"journal-article","created":{"date-parts":[[2017,4,26]],"date-time":"2017-04-26T13:42:06Z","timestamp":1493214126000},"page":"187","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Multicomponent and Longitudinal Imaging Seen as a Communication Channel\u2014An Application to Stroke"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2225-7371","authenticated-orcid":false,"given":"Mathilde","family":"Giacalone","sequence":"first","affiliation":[{"name":"Univ.Lyon, INSA-Lyon, Universit\u00e9 Claude Bernard Lyon 1, CNRS, Inserm, CREATIS UMR 5220, U1206, F-69621 Lyon, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Carole","family":"Frindel","sequence":"additional","affiliation":[{"name":"Univ.Lyon, INSA-Lyon, Universit\u00e9 Claude Bernard Lyon 1, CNRS, Inserm, CREATIS UMR 5220, U1206, F-69621 Lyon, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Emmanuel","family":"Grenier","sequence":"additional","affiliation":[{"name":"ENS-Lyon, UMR CNRS 5669 \u2018UMPA\u2019, and INRIA Alpes, project NUMED, F-69364 Lyon, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"David","family":"Rousseau","sequence":"additional","affiliation":[{"name":"Univ.Lyon, INSA-Lyon, Universit\u00e9 Claude Bernard Lyon 1, CNRS, Inserm, CREATIS UMR 5220, U1206, F-69621 Lyon, France"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2017,4,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"379","DOI":"10.1002\/j.1538-7305.1948.tb01338.x","article-title":"A Mathematical Theory of Communication","volume":"27","author":"Shannon","year":"1948","journal-title":"Bell Syst. 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