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Table 4 Classification results using Convex-NMF for DR prior to classification with Fisher LDA.

From: Non-negative matrix factorisation methods for the spectral decomposition of MRS data from human brain tumours

LTE

     

A2, NO(2SS)

A2, ME, NO(3SS)

A2, GL, NO(3SS)

A2, MM, NO(3SS)

A2, AG, NO(4SS)

A2, AG, MM(4SS)

Total:100% ± 0.0

Total:92.6% ± 3.3

Total:85.1% ± 3.4

Total:97.7% ± 1.6

Total:90.9% ± 2.4

Total:79.4% ± 3.0

A2:100% ± 0.0

A2:100% ± 0.0

A2:84.9% ± 8.5

A2:94.8% ± 5.0

A2:100% ± 0.0

A2:94.9% ± 5.2

NO:100% ± 0.0

ME:84.1% ± 6.8

GL:82.3% ± 4.3

GL:98.2% ± 1.9

AG:88.0% ± 3.1

AG:72.5% ± 4.3

 

NO:100% ± 0.0

NO:100% ± 0.0

NO:100% ± 0.0

NO:100% ± 0.0

MM:87.5% ± 4.3

STE

     

A2, NO(2SS)

A2, ME, NO(3SS)

A2, GL, NO(3SS)

A2, MM, NO(3SS)

A2, AG, NO(4SS)

A2, AG, MM(4SS)

Total:95.5% ± 3.1

Total:94.0% ± 2.6

Total:91.0% ± 2.5

Total:92.2% ± 2.7

Total:92.3% ± 2.0

TOTAL:87.7% ± 2.3

A2:91.2% ± 6.0

A2:86.3% ± 7.4

A2:82.5% ± 8.1

A2:86.3% ± 7.7

A2:81.9% ± 8.2

A2:95.5% ± 4.6

NO:100% ± 0.0

ME:95.0% ± 3.5

GL:90.9% ± 3.1

GL:91.5% ± 3.7

AG:92.8% ± 2.3

AG:86.3% ± 3.2

 

NO:100% ± 0.0

NO:100% ± 0.0

NO:100% ± 0.0

NO:100% ± 0.0

MM:87.7% ± 4.3

  1. Classification results (accuracy ± standard deviation) obtained with Fisher LDA (implemented in SpectraClassifier) for six diagnostic problems, from the source signals obtained by Convex-NMF, for data acquired at LTE and STE. Classifier results were validated through bootstrap. The number of source signals (SS) used in the experiments is indicated in parentheses