Automatic branch detection of the arterial system from abdominal aortic segmentation.

We present a new method to automatically identify the different arteries present in an abdominal aortic segmentation. In this approach, the arterial system is first represented by a vascular tree, extracted from the segmentation and containing the topologic and geometric features (branch position, b...

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Publicado en:Medical & Biological Engineering & Computing Vol. 60; no. 9; pp. 2639 - 2655
Autores principales: Riffaud, Sébastien, Ravon, Gwladys, Allard, Thibault, Bernard, Florian, Iollo, Angelo, Caradu, Caroline
Formato: Journal Article
Publicado: Springer Nature Sep2022
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Sep2022
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      pub: Springer Nature
      place: New York, New York
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        10.1007/s11517-022-02603-2
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        atl: Automatic branch detection of the arterial system from abdominal aortic segmentation.
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        au:
          Riffaud, Sébastien
          Ravon, Gwladys
          Allard, Thibault
          Bernard, Florian
          Iollo, Angelo
          Caradu, Caroline
        affil: Inria - Bordeaux Sud-Ouest, Team MEMPHIS, 33405, Talence, France
      sug:
        subj:
          Aortic Aneurysm, Abdominal
          Aorta, Abdominal
          Celiac Artery
          Renal Artery
      ab: We present a new method to automatically identify the different arteries present in an abdominal aortic segmentation. In this approach, the arterial system is first represented by a vascular tree, extracted from the segmentation and containing the topologic and geometric features (branch position, branch direction, branch length, branch diameter) of the arterial system. Then, the branches of the vascular tree are matched with the main arteries originating from the aorta: celiac artery, superior mesenteric artery, renal arteries and common iliac arteries. This match is determined by maximizing a similarity measure between the different branches and corresponding arteries. We evaluate this method on 239 segmentations obtained from 102 different patients. The results demonstrate the accuracy of the proposed method, capable of delivering an error of less than 2.5% for the identification of the celiac and superior mesenteric arteries, 8.4% for the renal arteries, and 2.1% for the common iliac arteries.
      pubtype: Academic Journal
      doctype: Journal Article
      ougenre: Article
    language: English
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