Abstract
In this paper, we describe how Active Shape Models (ASMs) have been used to accurately and robustly locate vertebrae in lateral Dual Energy X-ray Absorptiometry (DXA) images of the spine. DXA images are of low spatial resolution, and contain significant random and structural noise, providing a difficult challenge for object location methods. All vertebrae in the image were searched for simultaneously, improving robustness in location of individual vertebrae by making use of constraints on shape provided by the position of other vertebrae. We show that the use of ASMs with minimal user interaction allows accuracy to be obtained which is as good as that achievable by human operators, as well as high precision. Having located each vertebra, it is desirable to evaluate whether it has been located sufficiently accurately for shape measurements to be useful. We determined this on the basis of grey-level model fit, which was shown to usefully detect poorly located vertebrae, which should enable accuracy to be improved by rejecting proposed search solutions whose grey-level fit was poorer than a threshold. © 1997 Elsevier Science B.V.
Original language | English |
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Pages (from-to) | 575-581 |
Number of pages | 6 |
Journal | Image and Vision Computing |
Volume | 15 |
Issue number | 8 |
Publication status | Published - Aug 1997 |
Keywords
- Active shape models
- Segmentation
- Vertebral shape