The enhancement of radiotherapy verification images by an automated edge detection technique.
Adaptive histogram equalization techniques are known to be effective for the enhancement of contrast in portal images acquired during radiotherapy treatments. A significant drawback is the loss of definition on the edges of the treatment field. Analysis of this problem shows that it can be remedied by separating the treatment field from the background prior to the enhancement, and using only the pixels within the field boundary in the enhancement procedure. An edge extraction algorithm has been developed for delineating the treatment field in portal images, and consists of four modules that are applied to the original portal image in sequence. In the first step, edges are enhanced with a derivative of Gaussian operator that assures high response to the field edges relative to anatomical or other edges in the image. Pixels for which the response of the edge operator was the strongest are subsequently connected by an edge following algorithm to produce a raw contour of the field. In the last two steps the contour is refined by converting it into straight line segments and appending to the contour any parts of the field edge that might have been missed out during the initial edge following. The final contour encloses exclusively those pixels that belong to the treatment field, and the adaptive histogram equalization is applied selectively to this region. The combination of edge detection and selective enhancement was shown to produce images of superior contrast on the patient's anatomical features as well as accurate definition of treatment field edges.
Leszczynski
K W
KW
Department of Medical Physics, Manitoba Cancer Treatment and Research Foundation, Winnipeg, Canada.
Shalev
S
S
Cosby
N S
NS
D000465:Algorithms; D001322:Autoanalysis; D006801:Humans; D008433:Mathematics; D008953:Models, Anatomic; D011859:Radiography / Q000379:methods*; D011878:Radiotherapy / Q000379:methods*