Sinop Ali Kemal, Grady Leo
Department of Imaging and Visualization, Siemens Corporate Research, Princeton, NJ, USA.
Med Image Comput Comput Assist Interv. 2006;9(Pt 2):896-903. doi: 10.1007/11866763_110.
The Graph Cuts method of interactive segmentation has become very popular in recent years. This method performs at interactive speeds for smaller images/volumes, but an unacceptable amount of storage and computation time is required for the large images/volumes common in medical applications. The Banded Graph Cut (BGC) algorithm was proposed to drastically increase the computational speed of Graph Cuts, but is limited to the segmentation of large, roundish objects. In this paper, we propose a modification of BGC that uses the information from a Laplacian pyramid to include thin structures into the band. Therefore, we retain the computational efficiency of BGC while providing quality segmentations on thin structures. We make quantitative and qualitative comparisons with BGC on images containing thin objects. Additionally, we show that the new parameter introduced in our modification provides a smooth transition from BGC to traditional Graph Guts.
