Automatic extraction of 3d dynamic left ventricle model from 2d rotational angiocardiogram
MICCAI'11 Proceedings of the 14th international conference on Medical image computing and computer-assisted intervention - Volume Part III
Simultaneous segmentation of multiple closed surfaces using optimal graph searching
IPMI'05 Proceedings of the 19th international conference on Information Processing in Medical Imaging
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In this paper, we propose a novel method to convert segmentation of objects with quasi-periodic motion in 2D rotational cone beam projection images into an optimal 3D multiple interrelated surface detection problem, which can be solved by a graph search framework. The method is tested on lung tumor segmentation in projection images of mega-voltage cone beam CT (MVCBCT). A 4D directed graph is constructed based on an initialized tumor mesh model, where the cost value for this graph is computed from the point location of a silhouette outline of projected tumor mesh in 2D projection images. The method was first evaluated on four different sized phantom inserts (all above 1.9 cm in diameter) with a predefined motion of 3.0 cm to mimic the imaging of lung tumors. A dice coefficient of 0.87 ±0.03 and a centroid error of 1.94 ±1.31 mm were obtained. Results based on 12 MVCBCT scans from 3 patients obtained 0.91 ±0.03 for dice coefficient and 1.83 ±1.31 mm for centroid error, compared with a difference between two sets of independent manual contours of 0.89 ±0.03 and 1.61 ±1.19 mm, respectively.