Skull stripping using graph cuts.
Removal of non-brain tissues, particularly dura, is an important step in enabling accurate measurement of brain structures. Many popular methods rely on iterative surface deformation to fit the brain boundary and tend to leave residual dura. Similar to other approaches, the method proposed here uses intensity thresholding followed by removal of narrow connections to obtain a brain mask. However, instead of using morphological operations to remove narrow connections, a graph theoretic image segmentation technique was used to position cuts that isolate and remove dura. This approach performed well on both the standardized IBSR test data sets and empirically derived data. Compared to the Hybrid Watershed Algorithm (HWA; (Segonne et al., 2004)) the novel approach achieved an additional 10-30% of dura removal without incurring further brain tissue erosion. The proposed method is best used in conjunction with HWA as the errors produced by the two approaches often occur at different locations and cancel out when their masks are combined. Our experiments indicate that this combination can substantially decrease and often fully avoid cortical surface overestimation in subsequent segmentation.
Sadananthan
Suresh A
SA
School of Computer Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore.
Zheng
Weili
W
Chee
Michael W L
MW
Zagorodnov
Vitali
V
D000465:Algorithms; D001921:Brain / Q000033:anatomy & histology; D002555:Cerebrospinal Fluid; D005188:False Negative Reactions; D005189:False Positive Reactions; D007839:Functional Laterality / Q000502:physiology; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging; D008959:Models, Neurological; D015203:Reproducibility of Results; D012886:Skull / Q000033:anatomy & histology*