Composite MRA: statistical approach to generate an MR angiogram from multiple contrasts.

Kim, Dahan; Edjlali, Myriam; Turski, Patrick; Johnson, Kevin M

Kim, Dahan; Edjlali, Myriam; Turski, Patrick; Johnson, Kevin M.

Affiliation

Kim D; Department of Physics, University of Wisconsin, Madison, Wisconsin.
Edjlali M; Department of Medical Physics, University of Wisconsin, Madison, Wisconsin.
Turski P; Department of Neuroradiology, Université Paris-Descartes-Sorbonne-Paris-Cité, IMABRAIN-INSERM-UMR1266, DHU-Neurovasc, Centre Hospitalier Sainte-Anne, Paris, France.
Johnson KM; Department of Radiology, University of Wisconsin, Madison, Wisconsin.

Magn Reson Med ; 83(3): 830-843, 2020 03.

Article in En | MEDLINE | ID: mdl-31556170

Subject(s)

Image Processing, Computer-Assisted/methods; Magnetic Resonance Angiography; Adult; Aged; Aged, 80 and over; Artifacts; Bayes Theorem; Carotid Artery, Internal/diagnostic imaging; Contrast Media; False Positive Reactions; Female; Humans; Image Enhancement/methods; Male; Middle Aged; Pattern Recognition, Automated; Probability; Sensitivity and Specificity

Key words

Bayesian statistics; MR angiography; artifact suppression; multiple contrasts; vessel segmentation

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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Image Processing, Computer-Assisted / Magnetic Resonance Angiography Type of study: Diagnostic_studies Limits: Adult / Aged / Aged80 / Female / Humans / Male / Middle aged Language: En Journal: Magn Reson Med Journal subject: DIAGNOSTICO POR IMAGEM Year: 2020 Type: Article

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