1. A method for Ileo-Cecal Valve (ICV) detection in an input 3D computed tomography (CT) volume, comprising: detecting initial box candidates for the ICV based on an ICV orifice in said input 3D CT volume; and detecting a box bounding the ICV in said 3D CT volume by sequentially detecting possible locations, scales, and orientations of the box bounding the ICV using incremental parameter learning based on said initial box candidates.
1. A method for Ileo-Cecal Valve (ICV) detection in an input 3D computed tomography (CT) volume, comprising: detecting initial box candidates for the ICV based on an ICV orifice in said input 3D CT volume; and detecting a box bounding the ICV in said 3D CT volume by sequentially detecting possible locations, scales, and orientations of the box bounding the ICV using incremental parameter learning based on said initial box candidates. 3. The method of claim 1 , wherein said step of detecting a box bounding the ICV in said 3D CT volume comprises: generating a plurality of first testing boxes by shifting a center location of each of said initial box candidates; detecting a number of said first testing boxes as ICV position box candidates using a first trained classifier; generating a plurality of second testing boxes by varying a scale of each of said ICV position box candidates; detecting a number of said second testing boxes as ICV position and scale box candidates using a second trained classifier; generating a plurality of third testing boxes by adding disturbances to an orientation of each of said ICV position and scale box candidates; and detecting one of said third testing boxes as the box bounding the ICV in said 3D CT volume.