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First, the feasibility of cNMF\u2010based segmentation of IVIM signals was investigated in both simulations and in vivo experiments. The cNMF analysis was independently performed for <jats:italic>S<\/jats:italic><jats:sub><jats:italic>0<\/jats:italic><\/jats:sub>\u2010normalized and scaled (by the difference between the maximum and minimum) IVIM signals, respectively. Segmentations of reduced diffusion (from <jats:italic>S<\/jats:italic><jats:sub><jats:italic>0<\/jats:italic><\/jats:sub>\u2010normalized IVIM signals) and decreased perfusion (from scaled IVIM signals) areas were performed using the corresponding cNMF pattern weight maps. Second, Monte Carlo simulations were performed for directional IVIM signals to investigate the relationship between the degree of vessel alignment and the direction of the diffusion gradient. Third, directional IVIM\u2010MRI experiments (<jats:italic>x<\/jats:italic>, <jats:italic>y<\/jats:italic> and <jats:italic>z<\/jats:italic> diffusion\u2010gradient directions, 20 <jats:italic>b<\/jats:italic> values at 7 T) were performed for normal (<jats:italic>n<\/jats:italic> = 4), sacrificed (<jats:italic>n<\/jats:italic> = 1, no flow) and ischemic stroke models (<jats:italic>n<\/jats:italic> = 4, locally reduced flow). The results showed that automatic segmentation of the hypoperfused lesion using cNMF analysis was more accurate than segmentation using the conventional double\u2010exponential fitting. Consistent with the simulation, the double\u2010exponential pattern of the IVIM signals was particularly strong in white matter and ventricle regions when the directional flows were aligned with the applied diffusion\u2010gradient directions. cNMF analysis of directional IVIM signals allowed robust automated segmentation of white matter, ventricle, vascular and hypoperfused regions in the ischemic brain. In conclusion, directional IVIM signals were simultaneously sensitive to diffusion and aligned flow and were particularly useful for automatically segmenting ischemic lesions via cNMF\u2010based pattern recognition.<\/jats:p>","DOI":"10.1002\/nbm.4268","type":"journal-article","created":{"date-parts":[[2020,2,18]],"date-time":"2020-02-18T01:30:32Z","timestamp":1581989432000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Pattern recognition analysis of directional intravoxel incoherent motion MRI in ischemic rodent brains"],"prefix":"10.1002","volume":"33","author":[{"given":"MinJung","family":"Jang","sequence":"first","affiliation":[{"name":"Department of Biomedical Engineering Ulsan National Institute of Science and Technology  Ulsan South Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Seokha","family":"Jin","sequence":"additional","affiliation":[{"name":"Department of Biomedical 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