TY - JOUR
T1 - On the creation of a segmentation library for digitized cervical and lumbar spine radiographs
AU - Gururajan, Arunkumar
AU - Kamalakannan, Sridharan
AU - Sari-Sarraf, Hamed
AU - Shahriar, Muneem
AU - Long, Rodney
AU - Antani, Sameer
N1 - Funding Information:
This work was supported by the Intramural Research Program of the National Institutes of Health (NIH) , National Library of Medicine (NLM) , and Lister Hill National Center for Biomedical Communications (LHNCBC) .
PY - 2011/6
Y1 - 2011/6
N2 - 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.
AB - 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.
KW - Cervical spine segmentation
KW - Lumbar spine segmentation
KW - Radiographic spine images
KW - Segmentation library
KW - Shape segmentation
UR - http://www.scopus.com/inward/record.url?scp=79953758195&partnerID=8YFLogxK
U2 - 10.1016/j.compmedimag.2010.11.006
DO - 10.1016/j.compmedimag.2010.11.006
M3 - Article
C2 - 21377835
AN - SCOPUS:79953758195
SN - 0895-6111
VL - 35
SP - 251
EP - 265
JO - Computerized Medical Imaging and Graphics
JF - Computerized Medical Imaging and Graphics
IS - 4
ER -