Use of the Hough transformation to detect lines and curves in pictures
Communications of the ACM
On the optimal detection of curves in noisy pictures
Communications of the ACM
Problem-Solving Methods in Artificial Intelligence
Problem-Solving Methods in Artificial Intelligence
Finding Picture Edges Through Collinearity of Feature Points
IEEE Transactions on Computers
Edge Detection in Simple Scenes Using a Priori Information
IEEE Transactions on Computers
A Parallel Mechanism for Describing Silhouettes
IEEE Transactions on Computers
Detection of Global Edges in Textured Images
IEEE Transactions on Computers
| Hi-index | 14.98 |
We describe a hierarchic computer procedure for the detection of nodular tumors in a chest radiograph. The radiograph is scanned and consolidated into several resolutions which are enhanced and analyzed by a hierarchic tumor recognition process. The hierarchic structure of the tumor recognition process has the form of a ladder-like decision tree. The major steps in the decision tree are: 1) find the lung regions within the chest radiograph, 2) find candidate nodule sites (potential tumor locations) within the lung regions, 3) find boundaries for most of these sites, 4) find nodules from among the candidate nodule boundaries, and 5) find tumors from among the nodules. The first three steps locate potential nodules in the radiograph. The last two steps classify the potential nodules into nonnodules, nodules which are not tumors, and nodules which are tumors.