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Determination of Wall Strain in Model Cerebral Aneurysms by Image Registration

机译:通过图像配准测定模型脑动脉瘤中的壁菌株

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The rupture of intracranial aneurysms often has devastating consequences, and it is important to be able to identify those aneurysms that are at risk. One potential marker for imminent rupture might be strain in the aneurysm wall. The wall cannot be imaged directly, but its position can be inferred from the boundary of the fluid domain. We hypothesise that the strain in the wall of the aneurysm might be recoverable from systolic and diastolic images by a process of registration. In this paper we demonstrate that an in-house registration algorithm can accurately compute strains from simple binary images constructed from the finite element solution of strains in an aneurysm. The gold standard is the strain field generated from the finite element analysis.
机译:颅内动脉瘤的破裂通常具有毁灭性的后果,重要的是能够识别有风险的动脉瘤。一种迫在眉睫的破裂的潜在标记可能是动脉瘤壁的应变。墙壁不能直接成像,但是其位置可以从流体域的边界推断出来。我们假设动脉瘤壁中的应变可以通过注册过程从收缩系统和舒张图像中恢复。在本文中,我们证明了内部登记算法可以精确地计算由动脉瘤中菌株的有限元溶液构成的简单二进制图像的菌株。黄金标准是从有限元分析产生的应变场。

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