A TECHNIQUE FOR ANATOMIC FEATURE EXTRACTION AND 
TRACKING ON SEQUENTIAL DIGITAL X-RAY IMAGES 
Sean Curry 
Vexcel Corporation 
Boulder, Colorado USA 
J.M. Anderson 
University of California 
Berkeley, California USA 
ABSTRACT 
The Craniofacial Research Instrumentation Laboratory at the 
University of California, San Francisco, has for a number of 
years been developing instrumentation and software packages 
for the acquisition and display of biostereometric data. 
Stereo photographs and x-rays of the head are used to 
analyse growth and treatment effects during orthodontic 
treatment and orthognathic surgery. Recent efforts have been 
directed towards automating anatomic feature location and 
tracking on series of time-separated cranial x-rays. 
Two tests were performed to evaluate the potential 
accuracies that could be achieved in feature tracking. In 
both tests, a series of cranial x-rays was converted to 
digital images using a CID camera connected to a frame 
grabber and a small computer. The first test series 
consisted of a single x-ray image which was translated and 
rotated three times. The second series of images consisted 
of three actual cranial x-rays of a single subject, acquired 
over a period of approximately two years. 
A number of anatomic features, such as incisor edges and 
apexes of teeth, were manually selected on the first image 
of each series. The features were then automatically tracked 
on subsequent digital images, and their locations compared 
to those derived from direct manual digitizing of the 
original film images. 
1. INTRODUCTION 
There are many potential applications of image processing in 
photogrammetry. However, because of the complex nature of 
the problems involved in pattern recognition, image 
understanding, and scene analysis, progress towards 
completely automated vision systems in photogrammetry has 
been slow. 
There are applications where the problems can be well 
defined, and specific image analysis solutions applied. 
Rosenfeld states that, from a practical standpoint, 
successful applications of image analysis are likely to be 
of a focussed nature, where a 'specialist' system has been 
tailored to a specific domain, making use of methods 
designed especially for that domain /5/ 
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