Title :
A Gestalt-Guided Heuristic Boundary Follower for X-Ray Images of Lung Nodules
Author :
Sankar, P.V. ; Sklansky, J.
Author_Institution :
School of Engineering, University of California, Irvine, CA 92717.
fDate :
5/1/1982 12:00:00 AM
Abstract :
A ``piecewise heuristic´´ follower of the boundaries of difficult-to-notice nonoverlapping blobs in digitized images is described. The technique was tested on 324 X-ray images of candidate lung nodules from eight radiographs with good results. This technique is several times faster than earlier detectors of the boundaries of lung nodules, while maintaining good fidelity of the detected boundaries.
Keywords :
Cancer detection; Dynamic programming; Image edge detection; Lungs; Microcomputers; Pixel; Radiography; X-ray detection; X-ray detectors; X-ray imaging; Boundary follower; X-ray; circle detection; computational complexity; dynamic programming; edge detection; gestalt; heap data structure; heuristic search; image processing; lung nodule; pattern recognition; tumor;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
DOI :
10.1109/TPAMI.1982.4767253
