Department of Bioinformatics and Functional Genomics, University of Heidelberg, BIOQUANT, IPMB, and DKFZ Heidelberg, Germany.
Med Image Anal. 2012 Aug;16(6):1187-201. doi: 10.1016/j.media.2012.05.010. Epub 2012 Jun 21.
Accurate quantification of the morphology of vessels is important for diagnosis and treatment of cardiovascular diseases. We introduce a new joint segmentation and registration approach for the quantification of the aortic arch morphology that combines 3D model-based segmentation with elastic image registration. With this combination, the approach benefits from the robustness of model-based segmentation and the accuracy of elastic registration. The approach can cope with a large spectrum of vessel shapes and particularly with pathological shapes that deviate significantly from the underlying model used for segmentation. The performance of the approach has been evaluated on the basis of 3D synthetic images, 3D phantom data, and clinical 3D CTA images including pathologies. We also performed a quantitative comparison with previous approaches.
准确量化血管形态对于心血管疾病的诊断和治疗非常重要。我们引入了一种新的联合分割和配准方法，用于量化主动脉弓形态，该方法将基于模型的分割与弹性图像配准相结合。通过这种组合，该方法受益于基于模型的分割的鲁棒性和弹性配准的准确性。该方法可以处理广泛的血管形状，特别是与明显偏离用于分割的基础模型的病理性形状。该方法的性能已基于 3D 合成图像、3D 体模数据和包括病理学的临床 3D CTA 图像进行了评估。我们还与以前的方法进行了定量比较。
