On the creation of a segmentation library for digitized cervical and lumbar spine radiographs

In this paper, we address the issue of computer-assisted indexing in one specific case, i.e., for the 17,000 digitized images of the spine acquired during the National Health and Nutrition Examination Survey (NHANES). The crucial step in this process is to accurately segment the cervical and lumbar spine in the radiographic images. To that end, we have implemented a unique segmentation system that consists of a suite of spine-customized automatic and semi-automatic statistical shape segmentation algorithms. Using the aforementioned system, we have developed experiments to optimally generate a library of spine segmentations, which currently include 2000 cervical and 2000 lumbar spines. This work is expected to contribute toward the creation of a biomedical Content-Based Image Retrieval system that will allow retrieval of vertebral shapes by using query by image example or query by shape example.