Brain MR Image Segmentation Based on an Adaptive Combination of Global and Local Fuzzy Energy

<table class="table-group" id="tab2"><tr><td><table class="table"><tr><td class="thead-hr" colspan="5"><hr/></td></tr><tr class="thead"><td align="left">Image</td><td align="center">BCFCM</td><td align="center">sFCM</td><td align="center">CLIC</td><td align="center">Proposed algorithm</td></tr><tr><td class="thead-hr" colspan="5"><hr/></td></tr><tr><td align="left">Brain 1</td><td align="center">0.8268</td><td align="center">0.6552</td><td align="center">24.2894</td><td align="center">11.0917</td></tr><tr><td align="left">Brain 2</td><td align="center">0.7176</td><td align="center">0.4992</td><td align="center">21.2317</td><td align="center">9.9841</td></tr><tr class="table-tr"><td colspan="5"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

CPU time (seconds) comparison for the four algorithms.

Mathematical Problems in Engineering

tab2

Table 2

Table 2: Brain MR Image Segmentation Based on an Adaptive Combination of Global and Local Fuzzy Energy 