Hybrid Discrete Wavelet Transform and Gabor Filter Banks Processing for Features Extraction from Biomedical Images

<table class="table-group" id="tab4"><tr><td><table class="table"><tr><td class="thead-hr" colspan="4"><hr/></td></tr><tr class="thead"><td align="left"> </td><td align="center">Accuracy</td><td align="center">Specificity</td><td align="center">Sensitivity</td></tr><tr><td class="thead-hr" colspan="4"><hr/></td></tr><tr><td align="left">Mammograms</td><td align="center">68.03% (±0.01)</td><td align="center">100%</td><td align="center">0%</td></tr><tr><td align="left">Retina</td><td align="center">50.00% (±0.00)</td><td align="center">100%</td><td align="center">0%</td></tr><tr><td align="left">Brain MRI</td><td align="center">86.61% (±0.03)</td><td align="center">100%</td><td align="center">0%</td></tr><tr class="table-tr"><td colspan="4"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

SVM classification performance measures obtained with Gabor-based features.

Journal of Medical Engineering

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Table 4

Table 4: Hybrid Discrete Wavelet Transform and Gabor Filter Banks Processing for Features Extraction from Biomedical Images 