Data analysis of multivariate magnetic resonance images I. A principal component analysis approach

Chemometrics and Intelligent Laboratory Systems

Volumn 5, Issue 4, 1989, Pages 311-322

  Grahn, Hans ^a   Szeverenyi, Nikolaus M ^b   Roggenbuck, Mark W ^c   Delaglio, Frank ^d   Geladi, Paul ^e  

^a UNIVERSITY OF LAUSANNE   (Switzerland)

^b SUNY UPSTATE MEDICAL UNIVERSITY   (United States)

^c SYRACUSE UNIVERSITY   (United States)

^d New Methods Research Inc ^*  (United States)

^e UMEÅ UNIVERSITY   (Sweden)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER ANALYSIS; DATA ANALYSIS; METHODOLOGY; NUCLEAR MAGNETIC RESONANCE IMAGING; PRIORITY JOURNAL; THEORETICAL STUDY;

EID: 0024307805     PISSN: 01697439     EISSN: None     Source Type: Journal    
DOI: 10.1016/0169-7439(89)80030-9     Document Type: Article

References (12)

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6. Structural positions of predicted and known Cu-Zn ore indications
7. The application of principal component analysis to multivariate MRI data
8. The utility of principal component analysis for the image display of brain lesions. A preliminary, comparative study
9. Transformations producing information enhanced synthetic images
10. Principal component analysis
11. The elements of latent variable models: a cautionary lecture