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Cephalometric analysis is an important tool for orthodontic diagnosis. Atpresent, most cephalometric analysis is performed with the help of imageprocessing techniques. Hence, the resolution between millimeter and pixel isneeded with high accuracy. In cephalometric analysis, a scale is placed infront of patient's head when taking the radiograph. This study aims to developan algorithm to recognize the scale in cephalogram, locate the scale mark andcalculate the pixel-millimeter-ratio. First, a ROI is detected and croppedbased on regression tree voting. Second, an algorithm is employed in ROI todetect the corner points of the scale and rotate the scale to perfectlyvertical direction. Finally, a pixel tracing algorithm is employed to locatethe first and the last scale mark in order to calculate the pixel length of thecalibration. A novel method is proposed to adaptively assign the size andorientation of the image patches described by the SIFT vectors to ensureinvariance of scale and rotation of images. The algorithm is robust tointerference including tags, stickers and stain. A dataset consisting 163cephalograms is tested and the algorithm performs a 100% Success Detection Ratewithin the precision range of 1.0mm.

Automatic Calculation of Resolution in Lateral Cephalogram Based on Scale Mark Detection