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Level set based brain aneurysm capturing in 3D

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TLDR
A level set based surface capturing algorithm to first capture the aneurysms from the vascular tree is presented and applications to medical images are presented to show the accuracy, consistency and robustness of the method in capturing brain aneurYSms and volume quantification.
Abstract
Brain aneurysm rupture has been reported to be closely related to aneurysm size. The current method used to determine aneurysm size is to measure the dimension of the aneurysm dome and the width of the aneurysm neck. Since aneurysms usually have complicated shapes, using just the size of the aneurysm dome and neck may not be accurate and may overlook important geometrical information. In this paper we present a level set based surface capturing algorithm to first capture the aneurysms from the vascular tree. Since aneurysms are described by level set functions, volumes, curvatures and other geometric quantities of the aneurysm surface can easily be computed for medical studies. Experiments and comparisons with models used for capturing illusory contours in 2D images are performed. Applications to medical images are also presented to show the accuracy, consistency and robustness of our method in capturing brain aneurysms and volume quantification.

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Citations
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ReportDOI

Subjective surfaces: a geometric model for boundary completion

TL;DR: A geometric model and a computational method for segmentation of images with missing boundaries, and an algorithm which tries to build missing information on the basis of the given point of view and the available information as boundary data to the algorithm are presented.
Journal ArticleDOI

On a Level-Set Method for Ill-Posed Problems with Piecewise Nonconstant Coefficients

TL;DR: In this paper, a level-set-type method for solving ill-posed inverse problems is proposed, with the assumption that the solutions are piecewise, but not necessarily constant functions with unknown level sets and unknown level values.
Journal ArticleDOI

Clinical Treatment and Nursing Intervention Study of Clipping Treatment of Cerebral Aneurysm under the Health Model of Data Analysis

TL;DR: This paper designs a health model based on data analysis to clinically apply clipping surgery for cerebral aneurysm and combines the deep learning in the neural network to train the treatment plan under the data analysis health model.
Posted Content

On a level-set method for ill-posed problems with piecewise non-constant coefficients

TL;DR: In this paper, a level set type method for solving ill-posed problems with the assumption that the solutions are piecewise, but not necessarily constant functions with unknown level sets and unknown level values is proposed.
References
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Book

Level Set Methods and Dynamic Implicit Surfaces

TL;DR: A student or researcher working in mathematics, computer graphics, science, or engineering interested in any dynamic moving front, which might change its topology or develop singularities, will find this book interesting and useful.
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A Review of Image Denoising Algorithms, with a New One

TL;DR: A general mathematical and experimental methodology to compare and classify classical image denoising algorithms and a nonlocal means (NL-means) algorithm addressing the preservation of structure in a digital image are defined.
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Unruptured intracranial aneurysms: natural history, clinical outcome, and risks of surgical and endovascular treatment

TL;DR: Patients' age was a strong predictor of surgical outcome, and the size and location of an aneurysm predict both surgical and endovascular outcomes.
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A Variational Level Set Approach to Multiphase Motion

TL;DR: In this paper, a coupled level set method for the motion of multiple junctions (of, e.g., solid, liquid, and grain boundaries), which follows the gradient flow for an energy functional consisting of surface tension and bulk energies, is developed.
Journal ArticleDOI

Regular Article: A PDE-Based Fast Local Level Set Method

TL;DR: A fast method to localize thelevel set method of Osher and Sethian and address two important issues that are intrinsic to the level set method, which reduces the computational effort by one order of magnitude, works in as much generality as the original one, and is conceptually simple and easy to implement.
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