Paper
11 May 1994 High-resolution anisotropic 3D edge detector for medical images
Shih-Ping Liou, Ajit Singh
Author Affiliations +
Abstract
Advances in sensor and computer technology are resulting in an increased use of three-dimensional images in medical diagnosis. Three dimensional edge detection provides 3D anatomical representation that aids in planning and executing certain surgical procedures as well as in registering images of different modalities. Existing 3D edge detectors are 3D generalizations of 2D edge detectors. Most have limited resolution in boundary representation (subject to the resolution of imaging modality) and limited ability to directly deal with anisotropic sampling which occurs frequently in medical images. This paper presents a formal formulation of the 3D edge detection problem for anisotropically sampled images. Our approach differs from the previous approaches in the following ways: (1) a 3D edge detector is developed for data on anisotropic grids, (2) a modified version of the marching cube algorithm is used to locate the zero-crossings of the second-order derivatives, and (3) a connected component algorithm is developed for grouping zero- crossing surfaces into a set of disjoint surfaces. We show experimental results on many clinically acquired CT and MR images.
© (1994) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Shih-Ping Liou and Ajit Singh "High-resolution anisotropic 3D edge detector for medical images", Proc. SPIE 2167, Medical Imaging 1994: Image Processing, (11 May 1994); https://doi.org/10.1117/12.175065
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CITATIONS
Cited by 3 scholarly publications.
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KEYWORDS
3D image processing

Sensors

Algorithm development

Edge detection

Detection and tracking algorithms

Image processing

Medical imaging

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