Diagnosis System for Hepatocellular Carcinoma Based on Fractal Dimension of Morphometric Elements Integrated in an Artificial Neural Network

<table class="table-group" id="tab3"><tr><td><table class="table"><tr><td class="thead-hr" colspan="4"><hr/></td></tr><tr class="thead"><td align="left" rowspan="2">Identified as…</td><td align="center" colspan="3">Correct diagnosis</td></tr><tr class="thead"><td align="center">HCC</td><td align="center">LM</td><td align="center">Normal tissue</td></tr><tr><td class="thead-hr" colspan="4"><hr/></td></tr><tr><td align="left">HCC</td><td align="center">1044</td><td align="center">6</td><td align="center">0</td></tr><tr><td align="left">LM</td><td align="center">17</td><td align="center">1383</td><td align="center">0</td></tr><tr><td align="left">Normal tissue</td><td align="center">0</td><td align="center">0</td><td align="center">2450</td></tr><tr class="table-tr"><td colspan="4"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

Number of correct interpretations of random images by the second pathologist.

BioMed Research International

tab3

Table 3

Table 3: Diagnosis System for Hepatocellular Carcinoma Based on Fractal Dimension of Morphometric Elements Integrated in an Artificial Neural Network 

Table 3 | Diagnosis System for Hepatocellular Carcinoma Based on Fractal Dimension of Morphometric Elements Integrated in an Artificial Neural Network 