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Related Concept Videos

Aneurysm I: Introduction01:30

Aneurysm I: Introduction

An aortic aneurysm is a localized outpouching or dilation at a weak point in the artery wall. It may involve different parts of the aorta, such as the abdominal aorta, aortic arch, or thoracic aorta.Etiological factorsSeveral disorders are associated with aortic aneurysms.Congenital causes, such as primary connective tissue disorders like Marfan syndrome, impact the integrity and strength of connective tissues, notably affecting the aorta. Marfan syndrome is a genetic disorder that specifically...
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Related Experiment Video

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A Volumetric Method for Quantification of Cerebral Vasospasm in a Murine Model of Subarachnoid Hemorrhage
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Automatic aneurysm neck detection using surface Voronoi diagrams.

Rubén Cárdenes1, José María Pozo, Hrvoje Bogunovic

  • 1Center for Computational Imaging and Simulation Technologies in Biomedicine (CISTIB), Universitat Pompeu Fabra, 08018 Barcelona, Spain.

IEEE Transactions on Medical Imaging
|May 31, 2011
PubMed
Summary
This summary is machine-generated.

This study introduces an automated method for isolating saccular intracranial aneurysms. It uses a minimum cost path to consistently define the aneurysm neck, improving accuracy and efficiency in cerebral aneurysm analysis.

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Area of Science:

  • Neurosurgery
  • Medical Imaging
  • Computational Anatomy

Background:

  • Manual delineation of saccular intracranial aneurysms is prone to observer variability.
  • Consistent and accurate measurements are crucial for cerebral aneurysm analysis.
  • Existing methods lack automation and robustness in defining the aneurysm neck.

Purpose of the Study:

  • To develop an automatic approach for saccular intracranial aneurysm isolation.
  • To establish a consistent definition of the aneurysm neck using a minimum cost path.
  • To automate and accelerate the analysis of cerebral aneurysms.

Main Methods:

  • A minimum cost path algorithm is employed on a scalar field derived from vessel surface data.
  • A fast marching approach calculates the scalar field, using distance from the centerline bifurcation.
  • A surface Voronoi diagram constrains the neck computation to ensure correct aneurysm sac topology.

Main Results:

  • The proposed method provides consistent measurements across different datasets, overcoming inter- and intra-observer variability.
  • Validation against manual delineations in 26 cases demonstrates robustness and accuracy.
  • The approach successfully automates and speeds up the analysis of cerebral aneurysms.

Conclusions:

  • The automatic minimum cost path method offers a robust and efficient solution for saccular intracranial aneurysm isolation.
  • This technique enhances consistency in morphological measurements, aiding clinical diagnosis and treatment planning.
  • The automation of aneurysm analysis represents a significant advancement in neurovascular imaging.