Paper
5 May 2004 3D tumor measurement in cone-beam CT breast imaging
Zikuan Chen, Ruola Ning
Author Affiliations +
Abstract
Cone-beam CT breast imaging provides a digital volume representation of a breast. With a digital breast volume, the immediate task is to extract the breast tissue information, especially for suspicious tumors, preferably in an automatic manner or with minimal user interaction. This paper reports a program for three-dimensional breast tissue analysis. It consists of volumetric segmentation (by globally thresholding), subsegmentation (connection-based separation), and volumetric component measurement (volume, surface, shape, and other geometrical specifications). A combination scheme of multi-thresholding and binary volume morphology is proposed to fast determine the surface gradients, which may be interpreted as the surface evolution (outward growth or inward shrinkage) for a tumor volume. This scheme is also used to optimize the volumetric segmentation. With a binary volume, we decompose the foreground into components according to spatial connectedness. Since this decomposition procedure is performed after volumetric segmentation, it is called subsegmentation. The subsegmentation brings the convenience for component visualization and measurement, in the whole support space, without interference from others. Upon the tumor component identification, we measure the following specifications: volume, surface area, roundness, elongation, aspect, star-shapedness, and location (centroid). A 3D morphological operation is used to extract the cluster shell and, by delineating the corresponding volume from the grayscale volume, to measure the shell stiffness. This 3D tissue measurement is demonstrated with a tumor-borne breast specimen (a surgical part).
© (2004) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Zikuan Chen and Ruola Ning "3D tumor measurement in cone-beam CT breast imaging", Proc. SPIE 5367, Medical Imaging 2004: Visualization, Image-Guided Procedures, and Display, (5 May 2004); https://doi.org/10.1117/12.534528
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Tumors

3D metrology

Binary data

Breast

Tissues

3D image processing

Natural surfaces

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