A Novel Method for Enhanced Needle Localization Using Ultrasound-Guidance

In this paper, we propose a novel and fast method to localize and track needles during image-guided interventions. Our proposed method is comprised of framework of needle detection and tracking in highly noisy ultrasound images via level set and PDE (partial differential equation) based methods. Major advantages of the method are: (1) efficiency, the entire numerical procedure can be finished in real-time: (2) robustness, insensitive to noise in the ultrasound images and: (3) flexibility, the motion of the needle can be arbitrary. Our method will enhance the ability of medical care-providers to track and localize needles in relation to objects of interest during image-guided interventions.

Authors and Affiliations

1. Department of Mathematics, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA, 92093-0112

   Bin Dong

2. Department of Emergency Medicine, University of California Los Angeles, BOX 951777, 924 Westwood Blvd, Ste 300, Los Angeles, CA, 90095-1777

   Eric Savitsky

3. Department of Mathematics, University of California, Los Angeles, CA, 90095-1555

   Stanley Osher

Editors and Affiliations

1. Department of Computer Science and Engineering, University of Nevada, Reno, USA

   George Bebis

2. NASA Ames Research Center, Moffett Field, CA, USA

   Richard Boyle

3. Lawrence Berkeley National Laboratory, Berkeley, CA, USA

   Bahram Parvin

4. Desert Research Institute, Reno, NV, USA

   Darko Koracin

5. Graduate School of Science and Engineering, Saitama University, 255 Shimo-Okubo, Sakura-ku, Saitama-shi, 338-8570, Saitama, Japan

   Yoshinori Kuno

6. Institute for Infocomm Research, 21 Heng Mui Keng Terrace, P.O. Box, 119613, Singapore

   Junxian Wang

7. Department of Computer Science & Information Engineering, Tamkang University, Tamsui, Taipei, Taiwan, R.O.C.

   Jun-Xuan Wang

8. Microsoft Research, Redmond, WA, USA

   Junxian Wang

9. Department of Informatics, Univ. of Zurich, Winterthurerstr. 190, P.O. Box, 8057, Zurich, Switzerland

   Renato Pajarola

10. Lawrence Livermore National Laboratory, 94550, Livermore, CA, USA

    Peter Lindstrom

11. University of Applied Sciences Bonn-Rhein-Sieg, 53754, Sankt Augustin, Germany

    André Hinkenjann

12. Humana Inc., 40202, Louisville, KY, USA

    Miguel L. Encarnação

13. SCI Institute & School of Computing, University of Utah, 84112, Salt Lake City, UT, USA

    Cláudio T. Silva

14. Desert Research Institute, 89512, Reno, NV, USA

    Daniel Coming

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