Validation of magnetic resonance imaging (MRI) multispectral tissue classification.

The application of NASA multispectral image processing technology for analysis of Magnetic Resonance Imaging (MRI) scans has been studied. Software and hardware capability has been developed, and a statistical evaluation of multispectral analysis application to MRI scans of the head has been performed.

[1]  Anil K. Jain.  Fundamentals of Digital Image Processing , 2018, Control of Color Imaging Systems.

[2]  T. M. Lillesand,et al.  Remote Sensing and Image Interpretation , 1980 .

[3]  R. Congalton.  A Quantitative Method to Test for Consistency and Correctness in Photointerpretation , 1983 .

[4]  J R Brookeman,et al.  Identification and 3-D quantification of atherosclerosis using magnetic resonance imaging. , 1988, Computers in biology and medicine.

[5]  Mike James,et al.  Classification Algorithms , 1986, Encyclopedia of Machine Learning and Data Mining.

[6]  M W Vannier,et al.  Multispectral magnetic resonance image analysis. , 1987, Critical reviews in biomedical engineering.

[7]  John R. Jensen,et al.  Introductory Digital Image Processing: A Remote Sensing Perspective , 1986 .

[8]  G. H. Rosenfield,et al.  A coefficient of agreement as a measure of thematic classification accuracy. , 1986 .

[9]  B. Everitt,et al.  Large sample standard errors of kappa and weighted kappa. , 1969 .

[10]  N M Hylton,et al.  Information processing in magnetic resonance imaging. , 1986, Critical reviews in diagnostic imaging.

[11]  S. Meindl,et al.  Erste klinische Ergebnisse der Gewebecharakterisierung durch T1, T2 und Protonendichte bei der Kernspintomographie1, 2 , 1987 .

[12]  R. L. Butterfield,et al.  Multispectral analysis of magnetic resonance images. , 1985, Radiology.

[13]  Douglas L. Rickman,et al.  Magnetic resonance imaging multispectral tissue classification , 1988 .