Needle Segmentation Using 3D Quick Randomized Hough Transform

Author

Qiu, Wu ; Ding, Mingyue ; Yuchi, Ming

Author_Institution

Key Lab. of Educ. Minist. of China, Huazhong Univ. of Sci. & Technol., Wuhan

fYear

2008

fDate

1-3 Nov. 2008

Firstpage

449

Lastpage

452

Abstract

A quick 3D needle segmentation algorithm for 3D US data is described in this paper. The algorithm includes the 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 1 mm, and the computational time of segmentation with 35 MB data is within 1s.

Keywords

Hough transforms; biomedical ultrasonics; image segmentation; medical image processing; ultrasonic imaging; 3D quick randomized Hough transform; 3D ultrasound image; coarse-fine searching strategy; needle segmentation; water phantom; Artificial intelligence; Educational technology; Electrodes; Hemorrhaging; Image segmentation; Imaging phantoms; Intelligent networks; Needles; Radio frequency; Ultrasonic imaging; 3D Quick Randomized Hough Transform; 3D Ultrasound image; needle segmentation;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Networks and Intelligent Systems, 2008. ICINIS '08. First International Conference on

Conference_Location

Wuhan

Print_ISBN

978-0-7695-3391-9

Electronic_ISBN

978-0-7695-3391-9

Type

conf

DOI

10.1109/ICINIS.2008.41

Filename

4683261