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
  • [41] Robot-assisted 3D-TRUS guided prostate brachytherapy: System integration and validation
    Wei, ZP
    Wan, G
    Gardi, L
    Mills, G
    Downey, D
    Fenster, A
    MEDICAL PHYSICS, 2004, 31 (03) : 539 - 548
  • [42] Neighbor-constrained segmentation with level set based 3-D deformable models
    Yang, J
    Staib, LH
    Duncan, JS
    IEEE TRANSACTIONS ON MEDICAL IMAGING, 2004, 23 (08) : 940 - 948
  • [43] A shape-based statistical method to retrieve 2D TRUS-MR slice correspondence for prostate biopsy
    Mitra, Jhimli
    Srikantha, Abhilash
    Sidibe, Desire
    Marti, Robert
    Oliver, Arnau
    Llado, Xavier
    Ghose, Soumya
    Vilanova, Joan C.
    Comet, Josep
    Meriaudeau, Fabrice
    MEDICAL IMAGING 2012: IMAGE PROCESSING, 2012, 8314
  • [44] Rotationally resliced 3D prostate TRUS segmentation using convex optimization with shape priors
    Qiu, Wu
    Yuan, Jing
    Ukwatta, Eranga
    Fenster, Aaron
    MEDICAL PHYSICS, 2015, 42 (02) : 877 - 891
  • [45] 3-D segmentation of lung nodules in CT images based on improved level set method
    Min, Zhifang
    Jin, Renchao
    Song, Enmin
    Liu, Hong
    Wang, Xiaotong
    Hung, Chih-Cheng
    INFORMATION-AN INTERNATIONAL INTERDISCIPLINARY JOURNAL, 2011, 14 (04): : 1411 - 1418
  • [46] Binary morphological shape-based interpolation applied to 3-D tooth reconstruction
    Bors, AG
    Kechagias, L
    Pitas, I
    IEEE TRANSACTIONS ON MEDICAL IMAGING, 2002, 21 (02) : 100 - 108
  • [47] Fast automatic 3D liver segmentation based on a three-level AdaBoost-guided active shape model
    He, Baochun
    Huang, Cheng
    Sharp, Gregory
    Zhou, Shoujun
    Hu, Qingmao
    Fang, Chihua
    Fan, Yingfang
    Jia, Fucang
    MEDICAL PHYSICS, 2016, 43 (05) : 2421 - 2434
  • [48] Shape-based interpolation of binary 3-D images using morphological skeletonization
    Chatzis, Vassilios
    Pitas, Ioannis
    International Conference on Multimedia Computing and Systems -Proceedings, 1999, 2 : 939 - 943
  • [49] Automatic 4D endocardium segmentation using hierarchical registration and model guided level set segmentation
    Fritscher, KD
    Pilgram, R
    Schubert, R
    CARS 2005: COMPUTER ASSISTED RADIOLOGY AND SURGERY, 2005, 1281 : 212 - 217
  • [50] Multi-atlas-based Automatic 3D Segmentation for Prostate Brachytherapy in Transrectal Ultrasound Images
    Nouranian, Saman
    Mahdavi, S. Sara
    Spadinger, Ingrid
    Morris, William J.
    Salcudean, S. E.
    Abolmaesumi, P.
    MEDICAL IMAGING 2013: IMAGE-GUIDED PROCEDURES, ROBOTIC INTERVENTIONS, AND MODELING, 2013, 8671