Reconstruction of Patient-Specific Cerebral Aneurysm Model Through Image Segmentation

Abstract

The diagnostic assessment of cerebrovascular disease makes use of computational simulation as a predicting tool to determine hemodynamics factor contributing to the disease from patient-specific models which imitate the actual shape of the object of interest. However, the patient-specific models are generally reconstructed from the medical images subjectively. Image segmentation is commonly performed to produce object of interest with high visualization. In order to produce patient-specific anatomical model, a systematic adjustment on image intensity was performed in this study. This paper tends to present the reconstruction of three-dimensional (3D) patient-specific cerebral aneurysm model through systematic image segmentation by using threshold coefficients, \(C_{thres}\) of 0.2, 0.3, 0.4, 0.5, and 0.6. 25 models were extracted from digital subtraction angiography (DSA) images. The results show that there is an obvious physical change of geometry on the models reconstructed with \(C_{thres}\) of 0.5 and 0.6, especially on the artery branch. The models reconstructed with \(C_{thres}\) of 0.2 to 0.4 are considered sufficient in term of arterial geometry configuration and they would be opted for further computational study.KeywordsCerebral aneurysmModel reconstructionSegmentationThreshold coefficient