Characterization of lung nodules

摘要

A method of identifying nodules in radiological images, said method comprising: (a) obtaining a radiological image; (b) selecting a sub-image centered around a candidate location; (c) dividing the sub-image into a rectangular array of cells; (d) calculating absolute values of Intensity Differences id(k) according to a Fractional Brownian Motion (FBM) calculation equation: ${\mathrm{id}}_{\left(k\right)}=\left[\begin{array}{c}\frac{\sum _{x=0}^{N-1}\sum _{y=0}^{N-k-1}I\left(x,y\right)-I\left(x,y+k\right)}{4N\left(N-k\right)}+\\ \frac{\sum _{y=0}^{N-1}\sum _{x=0}^{N-k-1}I\left(x,y\right)-I\left(x+k,y\right)}{4N\left(N-k\right)}+\\ \frac{\sum _{x=0}^{N-1-k}\sum _{y=0}^{N-k-1}I\left(x,y\right)-I\left(x+k,y+k\right)}{4{\left(N-k\right)}^2}+\\ \frac{\sum _{x=0}^{N-1-k}\sum _{y=0}^{N-k-1}I\left(x,N-y\right)-I\left(x+k,N-\left(y+k\right)\right)}{4{\left(N-k\right)}^2}\end{array}\right],$ for k=1 to s; (e) calculating a NFBM feature, f(k), for each id(k): f(k)=log(id(k))-log(id(1); (f) integrating f(k), over k=1 to s; (i) classifying the cells into intensity contrast classes, according to intensity contrast between each cell and its neighbors, and the integration result; (k) remapping each cell of the sub-image according to its contrast class, and (m) determining the shape of the region of high-contrast cells in the sub-image, wherein an annular shape identifies a nodule.