Skeleton Marching-based Parallel Vascular Geometry Reconstruction Using Implicit Functions

Qi, Quan; Li, Qing De; Cheng, Yongqiang; Hong, Qing Qi

Abstract

Fast high-precision patient-specific vascular tissue and geometric structure reconstruction is an essential task for vascular tissue engineering and computer-aided minimally invasive vascular disease diagnosis and surgery. In this paper, we present an effective vascular geometry reconstruction technique by representing a highly complicated geometric structure of a vascular system as an implicit function. By implicit geometric modelling, we are able to reduce the complexity and level of difficulty of this geometric reconstruction task and turn it into a parallel process of reconstructing a set of simple short tubular-like vascular sections, thanks to the easy-blending nature of implicit geometries on combining implicitly modelled geometric forms. The basic idea behind our technique is to consider this extremely difficult task as a process of team exploration of an unknown environment like a cave. Based on this idea, we developed a parallel vascular modelling technique, called Skeleton Marching, for fast vascular geometric reconstruction. With the proposed technique, we first extract the vascular skeleton system from a given volumetric medical image. A set of sub-regions of a volumetric image containing a vascular segment is then identified by marching along the extracted skeleton tree. A localised segmentation method is then applied to each of these sub-image blocks to extract a point cloud from the surface of the short simple blood vessel segment contained in the image block. These small point clouds are then fitted with a set of implicit surfaces in a parallel manner. A high-precision geometric vascular tree is then reconstructed by blending together these simple tubular-shaped implicit surfaces using the shape-preserving blending operations. Experimental results show the time required for reconstructing a vascular system can be greatly reduced by the proposed parallel technique.

Citation

Qi, Q., Li, Q. D., Cheng, Y., & Hong, Q. Q. (2020). Skeleton Marching-based Parallel Vascular Geometry Reconstruction Using Implicit Functions. International Journal of Automation and Computing, 17(1), 30-43. https://doi.org/10.1007/s11633-019-1189-4

• Journal Article Type: Article
• Acceptance Date: Jun 12, 2019
• Online Publication Date: Sep 10, 2019
• Publication Date: Feb 1, 2020
• Deposit Date: Apr 16, 2020
• Publicly Available Date: Apr 17, 2020
• Journal: International Journal of Automation and Computing
• Print ISSN: 1476-8186
• Electronic ISSN: 1751-8520
• Publisher: Springer Verlag
• Peer Reviewed: Peer Reviewed
• Volume: 17
• Issue: 1
• Pages: 30-43
• DOI: https://doi.org/10.1007/s11633-019-1189-4
• Keywords: Vascular geometric reconstruction; Implicit modelling; Parallel computing; High-performance; High-accuracy
• Public URL: https://hull-repository.worktribe.com/output/2667823
• Publisher URL: https://link.springer.com/article/10.1007/s11633-019-1189-4
• Additional Information: Received: 11 March 2019; Accepted: 12 June 2019; First Online: 10 September 2019