Pit Pattern Classification in Colonoscopy using Wavelets - WaveLab

5.2 Results
Pit Pattern Type Non-Neoplastic Neoplastic
k-NN
Non-Neoplastic 54 45
Neoplastic 25 74
SVM
Non-Neoplastic 57 42
Neoplastic 21 78
Table 5.12: Result distribution matrices for WT for 2 classes (Pit pattern images)
Pit Pattern Type I II III-L III-S IV V
k-NN
I 61 9 8 0 21 0
II 14 36 14 0 35 0
III-L 33 8 33 0 23 0
III-S 25 0 50 0 25 0
IV 19 17 8 0 53 0
V 12 24 8 0 56 0
SVM
I 47 19 17 0 16 0
II 17 43 12 1 22 1
III-L 22 8 33 0 33 1
III-S 8 0 41 8 41 0
IV 14 16 17 0 47 3
V 16 16 20 0 36 12
Table 5.13: Result distribution matrices for WT for 6 classes (Pit pattern images)
The tables 5.12 and 5.13 show the result distribution matrices for the two classes case
and the six classes case, respectively, using pit pattern images. For the two classes case, as
already stated above, we observe significantly better classification results for the neoplastic
images. For the six classes case we again observe a poor classification performance for pit
pattern types III-S and V, just like in the previous two methods.
The method has been tested with the outex images too, which again resulted in excellent
classification results, as can been seen in the tables 5.4 and 5.5. In the two classes case the
total classification result was 100% for the k-NN classifier as well as for the SVM classifier.
In the six classes case the classification result was 98% for the k-NN classifier and only
slightly below 100% for some separate classes. The result achieved with the SVM classifier
is pretty similar with an overall classification result of nearly 100%.
The result distribution matrix for the two classes case is a diagonal matrix, containing
100’s only on the main diagonal and zero at all other positions in the matrix. In the six
79