Localizing contour points for indexing an X-ray image retrieval system

Vertebra shape can effectively describe various pathologies found in spine X-ray images. There are some critical regions on the shape contour which help determine whether the shape is pathologic or normal. We selected a subset of 250 segmented vertebra boundaries for study from a collection of 17,000 digitized X-rays of cervical and lumbar spine taken as a part of the second National Health and Nutrition Examination Survey (NHANES II). A board certified expert radiologist marked nine morphometric landmark points on the contour of these cervical and lumbar images. Image indexing could mimic the model used by the radiologists to mark the images, e.g. 6-, 9-, or 10-point, thereby improve the query and retrieval of vertebra shapes from the image database. In this paper, we present a technique to automatically select nine points from the boundary contour. The comparison between two 9-point models using the L/sub 2/ distance and retrieval rank results derived respectively from the 9-point model marked by the expert and the 9-point model selected with our algorithm provides a good measure of how well the two models match.