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Cerebral aneurysm is a weak spot in a blood vessel that usually enlarges. Nowadays, cerebral aneurysm detection method is still being done manually by visually observing 2D or 3D medical images (CTA). The main purpose of this paper is to design a method of cerebral aneurysm detection and classify different vascular geometry with color indicator. The method developed was based on curvature analysis...
In this work, we present a novel content-based 3D shape retrieval system for Abdominal Aortic Aneurysm (AAA) rupture risk prediction. The algorithms incorporate shape context, RANdom SAmple Consensus (RANSAC) and thin plate spline (TPS) to achieve a reliable AAA rupture risk assessment system. Pre-labeled unruptured and ruptured cases (`-1' for unruptured and `1' for ruptured cases) are built and...
We present an iterative model-constrained graph-cut algorithm for the segmentation of Abdominal Aortic Aneurysm (AAA) thrombus. Given an initial segmentation of the aortic lumen, our method automatically segments the thrombus by iteratively coupling intensity-based graph min-cut segmentation and geometric parametric model fitting. The geometric model effectively constrains the graph min-cut segmentation...
The rupture of intracranial aneurysms is associated to significant morbidity and mortality rates. Although the mechanisms triggering this event are still unclear, morphology is among the factors considered by interventional neuroradiologists to decide treatment. The aim of this work is to explore the potential of morphological descriptors as rupture risk predictors in middle cerebral artery aneurysms...
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