1 July 2009 Segmentation of the pelvic girdle in pediatric computed tomographic images
Shantanu Banik, Rangaraj Mandayam Rangayyan, Graham Stewart Boag M.D., Randy Hoang Vu
Author Affiliations +
Abstract
Identification, localization, and segmentation of the thoracic, abdominal, and pelvic organs are important steps in computer-aided diagnosis, treatment planning, landmarking, and content-based retrieval of biomedical images. In this context, to aid the identification of the lower abdominal organs, to assist in image-guided surgery or treatment planning, to separate the abdominal cavity from the lower pelvic region, and to improve the process of localization of abdominal pathology, we propose methods to identify and segment automatically the pelvic girdle in pediatric computed tomographic (CT) images. The opening-by-reconstruction procedure was used for segmentation of the pelvic girdle. The methods include procedures to represent the pelvic surface by a quadratic model using linear least-squares estimation and to refine the model using deformable contours. The result of segmentation of the pelvic girdle was assessed quantitatively and qualitatively by comparing with the segmentation performed independently by a radiologist. On the basis of quantitative analysis with 13 CT exams of six patients, including a total of 277 slices with the pelvis, the average Hausdorff distance was determined to be 5.95 mm, and the average mean distance to the closest point (MDCP) was 0.53 mm. The average MDCP is comparable to the size of one pixel, on the average.
©(2009) Society of Photo-Optical Instrumentation Engineers (SPIE)
Shantanu Banik, Rangaraj Mandayam Rangayyan, Graham Stewart Boag M.D., and Randy Hoang Vu "Segmentation of the pelvic girdle in pediatric computed tomographic images," Journal of Electronic Imaging 18(3), 033005 (1 July 2009). https://doi.org/10.1117/1.3184783
Published: 1 July 2009
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CITATIONS
Cited by 1 scholarly publication.
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KEYWORDS
Image segmentation

Computed tomography

Bone

Fuzzy logic

Image processing

Skin

Tomography

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