Novel digital subtraction CT angiography based on 3D registration and refinement

Sung Min Kwon; Yong Sun Kim; Tae-Sung Kim; Dong Ik Kim M.D.; Jong Beom Ra

doi:10.1117/12.536101

12 May 2004 Novel digital subtraction CT angiography based on 3D registration and refinement

Sung Min Kwon, Yong Sun Kim, Tae-Sung Kim, Dong Ik Kim M.D., Jong Beom Ra

Proceedings Volume 5370, Medical Imaging 2004: Image Processing; (2004) https://doi.org/10.1117/12.536101
Event: Medical Imaging 2004, 2004, San Diego, California, United States

Abstract

Angiographic investigation using high-resolution CT images has become a useful tool for the sensitive examination of vascular diseases. However, CT angiography (CTA) does not allow a straightforward understanding of vascular structure, since some of interesting parts can be located near the high intensity skull base region. In this paper, a novel method for fast and automatic 3D digital subtraction CT angiography (DS-CTA) is presented to generate artifact-free angiograms. The proposed method consists of 3D registration to align a CT image to the CTA image, and subtraction and refinement to extract blood vessels. For efficient and accurate 3D registration, an NMI (normalized mutual information) based algorithm is adopted and its fast version is developed by introducing a new measure. The speed-up ratio of the proposed fast registration algorithm is about 1.74~3.01 compared with the conventional registration method. And to improve the subtracted image quality in the second step, a novel 3D refinement algorithm is suggested to effectively remove unwanted residuals. Experimental results of seven clinical CT/CTA head datasets demonstrate that cerebral vessels are well extracted from CTA images with almost no loss. The typical processing time is about 3~9 minutes depending on the image size in a PC with a 2.4GHz CPU.

Citation Download Citation

Sung Min Kwon, Yong Sun Kim, Tae-Sung Kim, Dong Ik Kim M.D., and Jong Beom Ra "Novel digital subtraction CT angiography based on 3D registration and refinement", Proc. SPIE 5370, Medical Imaging 2004: Image Processing, (12 May 2004); https://doi.org/10.1117/12.536101

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