AbstractID: 8964 Title: An Adaptive Marker Detection Algorithm For High Resolution a-Si
Portal Imagers
Precise patient positioning in EBRT has become more critical with the advent of IMRT and the ability for dose escalation. Reliable algorithms for
the automatic detection of fiducial markers from megavoltage portal images may be used to automate the process We present an adaptive
detection algorithm for gold markers in the prostate. The algorithm uses no pre-determined value or threshold but rather relies on contextual
values to extract “out of the ordinary” features. The algorithm begins by applying a binomial averaging filter to the entire image. Next, local
minima are found and for each one, a square region is extracted and the background intensity (the average plane) is removed. The modulus of the
gradient is then calculated in the region and once again the background is removed. The region is next thresholded at a gradient value determined
from the distribution of values (the value at half height of the mode). From the now black and white region, blobs are identified. The largest blob
is compared to the blob of an ideal marker (a ring shape) and a figure of merit is calculated from the numbers of pixels on and outside the ring.
High figure of merits identify markers. The algorithm has been tested on images acquired at 18 MeV with 2 MUs, on large and small fields, both
from AP and lateral views. Few false positives and no false negatives were declared, which makes the algorithm suitable for automation.