Inferior vena cava segmentation with parameter propagation and graph cut

Inferior vena cava segmentation with parameter propagation and graph cut Int J CARS (2017) 12:1481–1499 DOI 10.1007/s11548-017-1582-9 ORIGINAL ARTICLE Inferior vena cava segmentation with parameter propagation and graph cut 1 2 1 1 Zixu Yan · Feng Chen · Fa Wu · Dexing Kong Received: 13 November 2016 / Accepted: 29 March 2017 / Published online: 18 April 2017 © CARS 2017 Abstract metric distance (MSD), and the Hausdorff distance (MaxD). Purpose The inferior vena cava (IVC) is one of the vital The proposed method has achieved a Dice of 89.56 ±3.71%, veins inside the human body. Accurate segmentation of the an MSD of 0.80±0.33 mm, and a MaxD of 11.48±3.04 mm, IVC from contrast-enhanced CT images is of great impor- respectively, in our experiments. tance. This extraction not only helps the physician understand Conclusion The proposed approach can achieve a sound its quantitative features such as blood flow and volume, but performance with a relatively low computational cost and a also it is helpful during the hepatic preoperative planning. minimal user interaction. The proposed algorithm has high However, manual delineation of the IVC is time-consuming potential to be applied for the clinical applications in the and poorly reproducible. future. Methods In this paper, we propose a novel method International Journal of Computer Assisted Radiology and Surgery Springer Journals

Inferior vena cava segmentation with parameter propagation and graph cut

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Springer International Publishing
Copyright © 2017 by CARS
Medicine & Public Health; Imaging / Radiology; Surgery; Health Informatics; Computer Imaging, Vision, Pattern Recognition and Graphics; Computer Science, general
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