AUTOMATIC SHAPE-BASED LEVEL SET SEGMENTATION FOR NEEDLE TRACKING IN 3-D TRUS-GUIDED PROSTATE BRACHYTHERAPY

被引:20
|
作者
Yan, Ping [1 ]
Cheeseborough, John C., III [2 ]
Chao, K. S. Clifford [1 ,2 ]
机构
[1] Columbia Univ, Dept Radiat Oncol, New York, NY 10032 USA
[2] Weill Cornell Med Coll, Dept Radiat Oncol, New York, NY USA
来源
ULTRASOUND IN MEDICINE AND BIOLOGY | 2012年 / 38卷 / 09期
关键词
Brachytherapy; TRUS; Level set; Needle tracking; Prostate cancer; Real-time imaging; ULTRASOUND; LOCALIZATION; TRANSFORM;
D O I
10.1016/j.ultrasmedbio.2012.02.011
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
Prostate brachytherapy is an effective treatment for early prostate cancer. The success depends critically on the correct needle implant positions. We have devised an automatic shape-based level set segmentation tool for needle tracking in 3-D transrectal ultrasound (TRUS) images, which uses the shape information and level set technique to localize the needle position and estimate the endpoint of needle in real-time. The 3-D TRUS images used in the evaluation of our tools were obtained using a 2-D TRUS transducer from Ultrasonix (Richmond, BC, Canada) and a computer-controlled stepper motor system from Thorlabs (Newton, NJ, USA). The accuracy and feedback mechanism had been validated using prostate phantoms and compared with 3-D positions of these needles derived from experts' readings. The experts' segmentation of needles from 3-D computed tomography images was the ground truth in this study. The difference between automatic and expert segmentations are within 0.1 mm for 17 of 19 implanted needles. The mean errors of automatic segmentations by comparing with the ground truth are within 0.25 mm. Our automated method allows real-time TRUS-based needle placement difference within one pixel compared with manual expert segementation. (E-mail: ksc2119@columbia.edu) (c) 2012 World Federation for Ultrasound in Medicine & Biology.
引用
收藏
页码:1626 / 1636
页数:11
相关论文
共 50 条
  • [31] Needle and seed segmentation in intra-operative 3D ultrasound-guided prostate brachytherapy
    Ding, Mingyue
    Wei, Zhouping
    Gardi, Lori
    Downey, Donal B.
    Fenster, Aaron
    ULTRASONICS, 2006, 44 : E331 - E336
  • [32] A 3-D Ultrasound Robotic Prostate Brachytherapy System With Prostate Motion Tracking
    Hungr, Nikolai
    Baumann, Michael
    Long, Jean-Alexandre
    Troccaz, Jocelyne
    IEEE TRANSACTIONS ON ROBOTICS, 2012, 28 (06) : 1382 - 1397
  • [33] Adaptive Metal Artifacts Correction in 3D TRUS Image Guided Prostate Brachytherapy
    Yan, P.
    Chao, K.
    MEDICAL PHYSICS, 2011, 38 (06)
  • [34] Shape-based segmentation and tracking in 4D cardiac MR images
    Rueckert, D
    Burger, P
    CVRMED-MRCAS'97: FIRST JOINT CONFERENCE - COMPUTER VISION, VIRTUAL REALITY AND ROBOTICS IN MEDICINE AND MEDICAL ROBOTICS AND COMPUTER-ASSISTED SURGERY, 1997, 1205 : 43 - 52
  • [35] Prostate Segmentation in 3D TRUS Using Convex Optimization with Shape Constraint
    Qiu, Wu
    Yuan, Jing
    Ukwatta, Eranga
    Tessier, David
    Fenster, Aaron
    MEDICAL IMAGING 2013: IMAGE PROCESSING, 2013, 8669
  • [36] BREAST MASS SEGMENTATION ON BREAST MRI USING THE SHAPE-BASED LEVEL SET METHOD
    Huang, Chieh-Ling
    BIOMEDICAL ENGINEERING-APPLICATIONS BASIS COMMUNICATIONS, 2014, 26 (04):
  • [37] Semiautomatic 3-D prostate segmentation from TRUS images using spherical harmonics
    Tutar, Ismail B.
    Pathak, Sayan D.
    Gong, Lixin
    Cho, Paul S.
    Wallner, Kent
    Kim, Yongmin
    IEEE TRANSACTIONS ON MEDICAL IMAGING, 2006, 25 (12) : 1645 - 1654
  • [38] Level-set evolution with region competition: Automatic 3-D segmentation of brain tumors
    Ho, S
    Bullitt, E
    Gerig, G
    16TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOL I, PROCEEDINGS, 2002, : 532 - 535
  • [39] Shape Guided 3D Active Contour Model for Automatic and Accurate MRI Prostate Segmentation
    Zhao, Xin
    Li, Bo
    2014 IEEE LONG ISLAND SYSTEMS, APPLICATIONS AND TECHNOLOGY CONFERENCE (LISAT), 2014,
  • [40] 3D Automatic MRI Level Set Segmentation of Inner Ear Based on Statistical Shape Models Prior
    Zhu, Shanshan
    Gao, Wanrong
    Zhang, Yin
    Zheng, Jian
    Liu, Zhaobang
    Yuan, Gang
    2017 10TH INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING, BIOMEDICAL ENGINEERING AND INFORMATICS (CISP-BMEI), 2017,