Segmentation of the pelvic girdle in pediatric computed tomographic images

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, t...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Journal of electronic imaging 2009-07, Vol.18 (3), p.033005-0330011
Hauptverfasser: Banik, Shantanu, Rangayyan, Rangaraj M, Boag, Graham S, Vu, Randy H
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung: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 , and the average mean distance to the closest point (MDCP) was . The average MDCP is comparable to the size of one pixel, on the average.
ISSN:1017-9909
1560-229X
DOI:10.1117/1.3184783