1 July 2006 Method for the automatic detection and segmentation of the spinal canal in computed tomographic images
Rangaraj Mandayam Rangayyan, Hanford J. Deglint, Graham Stewart Boag M.D.
Author Affiliations +
Abstract
A method for the automatic 3-D segmentation of the spinal canal in computed tomographic (CT) images is presented. The method uses a priori radiological and anatomical information, mathematical morphology, and region-growing methods. The skin and peripheral fat structures are determined by delineating the air and other materials external to the body. Using the fat layer as a reference, the bone structure is segmented. The Hough transform for the detection of circles is applied to a cropped bone edge map that includes the thoracic vertebral structure. The centers of the detected circles are used to derive the information required for the fuzzy connectivity algorithm that is employed to segment the spinal canal. In a preliminary study, the method successfully segmented the spinal canal in eight CT volumes of four patients, with Hausdorff distances with reference to contours drawn independently by a radiologist in the range 1.7±0.8 mm.
©(2006) Society of Photo-Optical Instrumentation Engineers (SPIE)
Rangaraj Mandayam Rangayyan, Hanford J. Deglint, and Graham Stewart Boag M.D. "Method for the automatic detection and segmentation of the spinal canal in computed tomographic images," Journal of Electronic Imaging 15(3), 033007 (1 July 2006). https://doi.org/10.1117/1.2234770
Published: 1 July 2006
Lens.org Logo
CITATIONS
Cited by 24 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Image segmentation

Bone

Computed tomography

Fuzzy logic

3D image processing

Skin

Feature extraction

RELATED CONTENT


Back to Top