Special Feature

User Panel

My Panel

My Panel

Bookmark Science Articles

Recent News
Bookmark / Share This Science Site

Automatic anatomical labeling method of cerebral arteries in MR-angiography data set.

Automatic anatomical labeling method of cerebral arteries in MR-angiography data set. Research Abstract Details 

Research Abstract Table of Contents

Jump to the:

  • Abstract Text of This Paper
  • Journal Published
  • MeSH Keywords of This Abstract
  • Chemicals and Substances Used in this Paper
  • Grants and Granting Agency of this Research
  • Database Accession Numbers Used in this Paper
  • Related Papers
  • Related Research Tags
  • Rate this Research Paper
  • Automatic anatomical labeling method of cerebral arteries in MR-angiography data set. Abstract Text:

    akihiro takemuraAkihiro Takemura,masayuki suzukiMasayuki Suzuki,hajime harauchiHajime Harauchi,yusuke okumuraYusuke Okumura,

    To improve the accuracy and robustness of 2D/3D registration of digital subtraction angiography images and magnetic resonance angiography (MRA) data, we have developed an automatic method for anatomical labeling of the cerebral arteries in MRA data. The anatomical labeling method is a location-based method which segments an artery tree to branches and classifies the branches into labeled segments, i.e., internal carotid arteries (ICA), basilar artery (BA), middle cerebral arteries (MCA), A1 segments of the anterior cerebral artery (ACA(A1)), other segments of the anterior cerebral artery (ACA), posterior communication arteries (PcomA) and posterior cerebral arteries (PCA), according to their location. Arteries were extracted from MRA data for this labeling method by the region-growing technique. Fifteen cases were examined to evaluate the method accuracy. The number of correctly segmented voxels in each artery segment was determined, and the correct labeling percentage was calculated based on the total number of voxels of the artery. Mean percentages were as follows: ACA, 82.7%; Right (R-) ACA(A1), 47.1%; Left (L-) ACA(A1), 46.1%; R-MCA, 80.4%; L-MCA, 74.1%; R-PcomA, 0.0%; L-PcomA, 3.3%; R-PCA, 60.3%; LPCA, 66.9%; R-ICA, 90.7%; L-ICA, 90.7%; BA, 89.9%; and total arteries, 84.1%. The ACA, MCA, ICA and BA were consistently identified correctly.

    Automatic anatomical labeling method of cerebral arteries in MR-angiography data set. Publishing Authors By Initials

    a takemuraA Takemura,m suzukiM Suzuki,h harauchiH Harauchi,y okumuraY Okumura,

    For similar abstracts research abstracts see: abstracts research

    PUBMED ID PMID:

    MEDLINE DATE:

    Automatic anatomical labeling method of cerebral arteries in MR-angiography data set. Journal Published:

    PUBLICATION TYPE: Journal Article

    Journal: Igaku butsuri : Nihon Igaku Butsuri Gakkai kikansh

    VOLUME: 26

    Page Numbers: 187-98

    Journal Abbreviation:

    ISSN: 1345-5354

    DAY: 19

    MONTH: 07

    YEAR: 2006

    Automatic anatomical labeling method of cerebral arteries in MR-angiography data set. Information

    Number of References:

    LANGUAGE: eng

    NlmUniqueID: 101125977

    Automatic anatomical labeling method of cerebral arteries in MR-angiography data set. Keywords Mesh Terms:

    KEYWORDS:

    MESH TERMS:

    Chemical & Substance for Abstract: Automatic anatomical labeling method of cerebral arteries in MR-angiography data set. Information

    Substance Name:

    Registry Number:

    Grant and Affiliation Information for Automatic anatomical labeling method of cerebral arteries in MR-angiography data set.

    AFFILIATION: Division of Health Sciences, Graduate School of Medical Science, Kanazawa University, 5-11-80, Kodatsuno, Kanazawa 920-0942, Japan. at@mhs.mp.kanazawa-u.ac.jp.

    Country: Japan

    Japan Research PublicationJapan Research Publication

    AGENCY:

    GRANT:

    ACRONYM:

    MEDLINETA: Igaku Butsuri

    REFSOURCE:

    DATABASENAME:

    ACCESSION NUMBER:

    Number Hits: 0

    Automatic anatomical labeling method of cerebral arteries in MR-angiography data set Related Publications

     

    Molecular Station USER Menu

    Welcome to Molecular Station!

    You have to register before you can post on our forums or use our advanced features. Register Now! Its Free and Fast!

    Already registered? Login now below.

    User Name:

    Password:

    Already registered and Forgot your password? Click below to recover it.

    Recover Lost Password

    Join now - it's fast and free!

    Molecular Station is THE largest network of researchers, scientists and science lovers anywhere!

    Research Terms of Usage and Disclaimer
    Home
    Features

    Protocols

    DNA Forum

    Science Forum

    DNA Forum
    Biology Forum

    Science News


    [CaRP] XML error: Invalid document end at line 2

    For more click here:Science News