Blind Deconvolution for Ultrasound Sequences Using a Noninverse Greedy Algorithm

<table class="table-group" id="tab4"><tr><td><table class="table"><tr><td class="thead-hr" colspan="5"><hr/></td></tr><tr class="thead"><td align="left">  Criteria </td><td align="center"> Our alg. </td><td align="center"><svg height="16.3125" id="M103" style="vertical-align:-3.27605pt" version="1.1" viewbox="0 0 11.0375 16.3125" width="11.0375" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
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<g transform="matrix(.012,-0,0,-.012,4.637,16.25)"><path d="M384 0h-275v27q67 5 81.5 18.5t14.5 68.5v385q0 38 -7.5 47.5t-40.5 10.5l-48 2v24q85 15 178 52v-521q0 -55 14.5 -68.5t82.5 -18.5v-27z" id="x31"></path></g>
</svg>-norm</td><td align="center"> Wiener </td><td align="center"> TV-norm</td></tr><tr><td class="thead-hr" colspan="5"><hr/></td></tr><tr><td align="left"> RG </td><td align="center"> 15 </td><td align="center"> 15 </td><td align="center"> 3 </td><td align="center"> 1 </td></tr><tr class="table-tr"><td colspan="5"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

Resolution gain evaluation on measured signals.

International Journal of Biomedical Imaging

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Table 4

Table 4: Blind Deconvolution for Ultrasound Sequences Using a Noninverse Greedy Algorithm 