title: Prostate Segmentation in CT Images via Spatial-Constrained Transductive Lasso.
abstract: Accurate prostate segmentation in CT images is a significant yet challenging task for image guided radiotherapy. In this paper, a novel semi-automated prostate segmentation method is presented. Specifically, to segment the prostate in the current treatment image, the physician first takes a few seconds to manually specify the first and last slices of the prostate in the image space. Then, the prostate is segmented automatically by the proposed two steps: (i) The first step of prostate-likelihood estimation to predict the prostate likelihood for each voxel in the current treatment image, aiming to generate the3-D prostate-likelihood map by the proposed Spatial-COnstrained Transductive LassO (SCOTO); (ii) The second step of multi-atlases based label fusion to generate the final segmentation result by using the prostate shape information obtained from the planning and previous treatment images. The experimental result shows that the proposed method outperforms several state-of-the-art methods on prostate segmentation in a real prostate CT dataset, consisting of24patients with330images. Moreover, it is also clinically feasible since our method just requires the physician to spend a few seconds on manual specification of the first and last slices of the prostate.
authors: State Key Laboratory for Novel Software Technology, Nanjing University, China ; Department of Radiology and BRIC, UNC Chapel Hill, U.S.
authors: Yinghuan
authors: Y
authors: Shi
authors: Shu
authors: S
authors: Liao
authors: Yaozong
authors: Y
authors: Gao
authors: Daoqiang
authors: D
authors: Zhang
authors: Yang
authors: Y
authors: Gao
authors: Dinggang
authors: D
authors: Shen