Pit Pattern Classification in Colonoscopy using Wavelets - WaveLab
Pit Pattern Classification in Colonoscopy using Wavelets - WaveLab
Pit Pattern Classification in Colonoscopy using Wavelets - WaveLab
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List of Figures<br />
1.1 <strong>Pit</strong> pattern classification accord<strong>in</strong>g to Kudo et al. . . . . . . . . . . . . . . 3<br />
1.2 Images show<strong>in</strong>g 3D views of the different types of pit pattern accord<strong>in</strong>g to<br />
Kudo. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3<br />
1.3 Images show<strong>in</strong>g the different types of pit pattern. . . . . . . . . . . . . . . 4<br />
2.1 Different wavelet functions ψ . . . . . . . . . . . . . . . . . . . . . . . . . 8<br />
2.2 Pyramidal decomposition (a) and one possible best-basis wavelet packet decomposition<br />
(b) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15<br />
2.3 Different decomposition trees result<strong>in</strong>g from different cost functions us<strong>in</strong>g<br />
the Haar wavelet. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16<br />
2.4 Different decomposition trees result<strong>in</strong>g from different cost functions us<strong>in</strong>g<br />
the biorthogonal Daubechies 7/9 wavelet. . . . . . . . . . . . . . . . . . . 17<br />
3.1 The k-NN classifier for a 2-dimensional feature space. . . . . . . . . . . . 29<br />
3.2 The SVM classifier for two different 2-dimensional feature spaces. . . . . . 31<br />
4.1 An example image with its accord<strong>in</strong>g co-occurrence matrix . . . . . . . . . 40<br />
4.2 Different example quadtrees for distance measurement . . . . . . . . . . . 49<br />
4.3 An example quadtree . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50<br />
4.4 Illustration of the feature vector equalization for FEUNV . . . . . . . . . . 52<br />
4.5 Distance matrices for the two-class case . . . . . . . . . . . . . . . . . . . 56<br />
5.1 Example images taken from our test set of endoscopic images. . . . . . . . 62<br />
5.2 Example images taken from the Outex image database. . . . . . . . . . . . 64<br />
5.3 Results for the BB method (6 classes, k-NN, pit pattern images) . . . . . . 71<br />
5.4 Results for the BBS method (6 classes, SVM, pit pattern images) . . . . . . 74<br />
5.5 Results for the BBCB method (2 classes, k-NN, pit pattern images) . . . . . 76<br />
5.6 Results for the BBCB method (2 classes, SVM, pit pattern images) . . . . . 77<br />
5.7 Results for the BBCB method (6 classes, SVM, Outex images) . . . . . . . 78<br />
5.8 Results for the WT method (2 classes, k-NN, <strong>Pit</strong> pattern images) . . . . . . 80<br />
5.9 Results for the WT method (2 classes, SVM, <strong>Pit</strong> pattern images) . . . . . . 81<br />
5.10 Results for the LDB method (2 classes, k-NN, <strong>Pit</strong> pattern images) . . . . . 84<br />
5.11 Results for the LDB method (6 classes, k-NN, <strong>Pit</strong> pattern images) . . . . . 85<br />
5.12 Results for the LDB method (6 classes, k-NN, Outex images) . . . . . . . . 86<br />
5.13 Distance matrices for the two classes and the six classes case (<strong>Pit</strong> pattern<br />
images) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88<br />
5.14 Distance matrices for the two classes and the six classes case (Outex images) 89<br />
95