GrowCut-based fast tumor segmentation for 3D magnetic resonance images
Toshihiko Yamasaki, Tsuhan Chen, Masakazu Yagi, Toshinori Hirai, Ryuji Murakami · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2012
This paper presents a very fast segmentation algorithm based on the region-growing-based segmentation called GrowCut for 3D medical image slices. By the combination of four contributions such as hierarchical segmentation, voxel value quantization, skipping method, and parallelization, the computational time is drastically reduced from 507 seconds to 9.2-14.6 seconds on average for tumor segmentation of 256 x 256 x 200 MRIs.