Literature DB >> 15081495

Specially adapted interactive tools for an improved 3D-segmentation of the spine.

Jan Kaminsky1, Petra Klinge, Thomas Rodt, Martin Bokemeyer, Wolf Luedemann, Madjid Samii.   

Abstract

For imaging purposes of the spine, segmented image data provides the basis for a variety of modern clinical applications. However, the anatomical complex structure of the spine as well as the extensive degenerative bony deformations apparent in the clinical situation, generally complicate the application of a fully automated segmentation. To serve the special needs for image segmentation of the spine anatomy a newly developed software system is presented, that implements specially adapted interactive tools, taking its 'axis'-skeletal structure into account. A standardized protocol combines the newly developed interactive tools (rotation transformation, warped dissection plane) with standard segmentation tools to provide both a fast and accurate segmentation procedure. The introduced software environment has been valuable for the segmentation of cervical, thoracic and lumbar spines segments based on clinical routine and research images.

Entities:  

Mesh:

Year:  2004        PMID: 15081495     DOI: 10.1016/j.compmedimag.2003.12.001

Source DB:  PubMed          Journal:  Comput Med Imaging Graph        ISSN: 0895-6111            Impact factor:   4.790


  4 in total

Review 1.  A review of methods for quantitative evaluation of spinal curvature.

Authors:  Tomaz Vrtovec; Franjo Pernus; Bostjan Likar
Journal:  Eur Spine J       Date:  2009-02-27       Impact factor: 3.134

2.  Automated Fractured Bone Segmentation and Labeling from CT Images.

Authors:  Darshan D Ruikar; K C Santosh; Ravindra S Hegadi
Journal:  J Med Syst       Date:  2019-02-02       Impact factor: 4.460

3.  Groupwise multi-atlas segmentation of the spinal cord's internal structure.

Authors:  Andrew J Asman; Frederick W Bryan; Seth A Smith; Daniel S Reich; Bennett A Landman
Journal:  Med Image Anal       Date:  2014-02-05       Impact factor: 8.545

4.  An improved level set method for vertebra CT image segmentation.

Authors:  Juying Huang; Fengzeng Jian; Hao Wu; Haiyun Li
Journal:  Biomed Eng Online       Date:  2013-05-28       Impact factor: 2.819

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.