Needle Segmentation Using 3D Quick Randomized Hough Transform

Authors:
Wu Qiu;Mingyue Ding;Ming Yuchi
Affiliations:
-;-;-
Venue:
ICINIS '08 Proceedings of the 2008 First International Conference on Intelligent Networks and Intelligent Systems
Year:
2008

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Abstract

A quick 3D needle segmentation algorithm for 3D US data is described in this paper. The algorithm includesthe 3D Quick Randomized Hough Transform (3DGHT), which is based on the 3D Randomized Hough Transform and coarse-fine searching strategy. We tested it with water phantom. The results show that our algorithm works well in 3D US images with angular deviation less than 1 degree and position deviation less than 1mm, and the computational time of segmentation with 35MB data is within 1s.