Visual Three-Dimensional Reconstruction of Aortic Dissection Based on Medical CT Images
| Autor: | Qi Wang, Xiuyan Li, Shi Meichen, Qingliang Chen, Xiaojie Duan, Zhao He, Jianming Wang, Zuo Ruixue, Chen Dandan |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
Aortic arch
Article Subject Computer science 02 engineering and technology lcsh:Telecommunication 030218 nuclear medicine & medical imaging 03 medical and health sciences 0302 clinical medicine lcsh:TK5101-6720 Active shape model medicine.artery 0202 electrical engineering electronic engineering information engineering Media Technology medicine Computer vision Segmentation Electrical and Electronic Engineering Aortic dissection business.industry Communication Volume rendering medicine.disease Feature (computer vision) Descending aorta Ray casting 020201 artificial intelligence & image processing Artificial intelligence business |
| Zdroj: | International Journal of Digital Multimedia Broadcasting, Vol 2017 (2017) |
| ISSN: | 1687-7578 |
| DOI: | 10.1155/2017/3163759 |
| Popis: | With the rapid development of CT technology, especially the higher resolution of CT machine and a sharp increase in the amount of slices, to extract and three-dimensionally display aortic dissection from the huge medical image data became a challenging task. In this paper, active shape model combined with spatial continuity was adopted to realize automatic reconstruction of aortic dissection. First, we marked aortic feature points from big data sample library and registered training samples to build a statistical model. Meanwhile, gray vectors were sampled by utilizing square matrix, which set the landmarks as the center. Posture parameters of the initial shape were automatically adjusted by the method of spatial continuity between CT sequences. The contrast experiment proved that the proposed algorithm could realize accurate aorta segmentation without selecting the interested region, and it had higher accuracy than GVF snake algorithm (93.29% versus 87.54% on aortic arch, 94.30% versus 89.25% on descending aorta). Aortic dissection membrane was extracted via Hessian matrix and Bayesian theory. Finally, the three-dimensional visualization of the aortic dissection was completed by volume rendering based on the ray casting method to assist the doctors in clinical diagnosis, which contributed to improving the success rate of the operations. |
| Databáze: | OpenAIRE |
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