3d multi-scale line filter for segmentation and visualization of curvilinear structures in medical images

Yoshinobu Sato, Shin Nakajima, Hideki Atsumi, Thomas Roller, Guido Gerig, Shigeyuki Yoshida, Ron Kikinis

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    This paper describes a method for the enhancement of curvilinear structures like vessels and bronchi in 3D medical images. We develop a line-enhancement filter based on the eigenvalues of Hessian matrix aiming at both the discrimination of line structures from other structures and the recovery of original line structures from corrupted ones. The multi-scale responses of the line filters are integrated based on the equalization of noise level at each scale. The resulted multi-scale line filtered images provide significantly improved segmentation of curvilinear structures. The line-filtered images are also useful for the direct visualization of curvilinear structures by combining with a volume rendering technique even from conventional MR images. We show the usefulness of the method through the segmentation and visualization of vessels from MRA and MR images, and bronchi from CT images.

    Original languageEnglish (US)
    Title of host publicationCVRMed-MRCAS 1997 - 1st Joint Conference Computer Vision, Virtual Reality and Robotics in Medicine and Medical Robotics and Computer-Assisted Surgery, Proceedings
    PublisherSpringer Verlag
    Pages213-222
    Number of pages10
    Volume1205
    ISBN (Print)3540627340, 9783540627340
    StatePublished - 1997
    Event1st International Joint Conference on Computer Vision, Virtual Reality, and Robotics in Medicine and Medical Robotics and Computer Assisted Surgery, CVRMed-MRCAS 1997 - Grenoble, France
    Duration: Mar 19 1997Mar 22 1997

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume1205
    ISSN (Print)03029743
    ISSN (Electronic)16113349

    Other

    Other1st International Joint Conference on Computer Vision, Virtual Reality, and Robotics in Medicine and Medical Robotics and Computer Assisted Surgery, CVRMed-MRCAS 1997
    CountryFrance
    CityGrenoble
    Period3/19/973/22/97

    Fingerprint

    Medical Image
    Visualization
    Segmentation
    Filter
    Volume rendering
    Line
    Recovery
    Vessel
    Enhancement
    Volume Rendering
    Hessian matrix
    CT Image
    Equalization
    3D Image
    Discrimination
    Eigenvalue

    ASJC Scopus subject areas

    • Computer Science(all)
    • Theoretical Computer Science

    Cite this

    Sato, Y., Nakajima, S., Atsumi, H., Roller, T., Gerig, G., Yoshida, S., & Kikinis, R. (1997). 3d multi-scale line filter for segmentation and visualization of curvilinear structures in medical images. In CVRMed-MRCAS 1997 - 1st Joint Conference Computer Vision, Virtual Reality and Robotics in Medicine and Medical Robotics and Computer-Assisted Surgery, Proceedings (Vol. 1205, pp. 213-222). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1205). Springer Verlag.

    3d multi-scale line filter for segmentation and visualization of curvilinear structures in medical images. / Sato, Yoshinobu; Nakajima, Shin; Atsumi, Hideki; Roller, Thomas; Gerig, Guido; Yoshida, Shigeyuki; Kikinis, Ron.

    CVRMed-MRCAS 1997 - 1st Joint Conference Computer Vision, Virtual Reality and Robotics in Medicine and Medical Robotics and Computer-Assisted Surgery, Proceedings. Vol. 1205 Springer Verlag, 1997. p. 213-222 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1205).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Sato, Y, Nakajima, S, Atsumi, H, Roller, T, Gerig, G, Yoshida, S & Kikinis, R 1997, 3d multi-scale line filter for segmentation and visualization of curvilinear structures in medical images. in CVRMed-MRCAS 1997 - 1st Joint Conference Computer Vision, Virtual Reality and Robotics in Medicine and Medical Robotics and Computer-Assisted Surgery, Proceedings. vol. 1205, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 1205, Springer Verlag, pp. 213-222, 1st International Joint Conference on Computer Vision, Virtual Reality, and Robotics in Medicine and Medical Robotics and Computer Assisted Surgery, CVRMed-MRCAS 1997, Grenoble, France, 3/19/97.
    Sato Y, Nakajima S, Atsumi H, Roller T, Gerig G, Yoshida S et al. 3d multi-scale line filter for segmentation and visualization of curvilinear structures in medical images. In CVRMed-MRCAS 1997 - 1st Joint Conference Computer Vision, Virtual Reality and Robotics in Medicine and Medical Robotics and Computer-Assisted Surgery, Proceedings. Vol. 1205. Springer Verlag. 1997. p. 213-222. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
    Sato, Yoshinobu ; Nakajima, Shin ; Atsumi, Hideki ; Roller, Thomas ; Gerig, Guido ; Yoshida, Shigeyuki ; Kikinis, Ron. / 3d multi-scale line filter for segmentation and visualization of curvilinear structures in medical images. CVRMed-MRCAS 1997 - 1st Joint Conference Computer Vision, Virtual Reality and Robotics in Medicine and Medical Robotics and Computer-Assisted Surgery, Proceedings. Vol. 1205 Springer Verlag, 1997. pp. 213-222 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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    abstract = "This paper describes a method for the enhancement of curvilinear structures like vessels and bronchi in 3D medical images. We develop a line-enhancement filter based on the eigenvalues of Hessian matrix aiming at both the discrimination of line structures from other structures and the recovery of original line structures from corrupted ones. The multi-scale responses of the line filters are integrated based on the equalization of noise level at each scale. The resulted multi-scale line filtered images provide significantly improved segmentation of curvilinear structures. The line-filtered images are also useful for the direct visualization of curvilinear structures by combining with a volume rendering technique even from conventional MR images. We show the usefulness of the method through the segmentation and visualization of vessels from MRA and MR images, and bronchi from CT images.",
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