A Generalized Gamma Mixture Model for Ultrasonic Tissue Characterization

<table>Undirected graph. The nodes represent a random variable <svg height="11.175" id="M461" style="vertical-align:-0.0pt" version="1.1" viewbox="0 0 13.5875 11.175" width="13.5875" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
<g transform="matrix(.017,-0,0,-.017,.062,11.113)"><path d="M775 650l-6 -28q-60 -6 -81.5 -16t-61.5 -54l-175 -191l125 -243q30 -58 48.5 -71t82.5 -19l-5 -28h-275l7 28l35 4q31 4 37 12t-6 34l-108 216q-140 -165 -177 -219q-16 -22 -10.5 -30.5t41.5 -13.5l22 -3l-7 -28h-244l8 28q52 4 75 15.5t67 52.5q48 46 206 231
l-110 215q-26 51 -44 63t-72 17l6 28h250l-6 -28l-27 -4q-30 -5 -35 -10t3 -27q17 -43 95 -190q70 78 154 185q15 21 10 29.5t-33 12.5l-30 4l5 28h236z" id="x1D44B"></path></g>
</svg> and the edges’ relationships between nodes. Each random variable can be classified as a tissue class <svg height="13.6375" id="M462" style="vertical-align:-1.97925pt" version="1.1" viewbox="0 0 7.8874998 13.6375" width="7.8874998" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
<g transform="matrix(.017,-0,0,-.017,.062,11.113)"><path d="M434 650l-5 -28q-60 -8 -75 -20.5t-25 -69.5l-71 -395q-20 -107 -57.5 -168t-106.5 -94q-40 -18 -61 -20l-10 32q77 23 113 108q21 50 41 160l68 377q10 57 -1.5 69.5t-76.5 20.5l6 28h261z" id="x1D43D"></path></g>
</svg>.</table>

Computational and Mathematical Methods in Medicine

fig17

Figure 17

Figure 17: A Generalized Gamma Mixture Model for Ultrasonic Tissue Characterization 