Cortical Surface Reconstruction Using a Topology Preserving Geometric Deformable Model
MMBIA '01 Proceedings of the IEEE Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA'01)
Consistent 4D cortical thickness measurement for longitudinal neuroimaging study
MICCAI'10 Proceedings of the 13th international conference on Medical image computing and computer-assisted intervention: Part II
Accurate and consistent 4D segmentation of serial infant brain MR images
MBIA'11 Proceedings of the First international conference on Multimodal brain image analysis
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Accurate segmentation of the brain MR images plays an important role in investigation of neurodegenerative changes in the cerebral cortex. However, most of the previous algorithms were proposed for segmentation of 3D images and few studies have taken the temporal consistency of cortical-thickness changes into account during the longitudinal studies. In this paper, we propose a 4D segmentation framework for the adult brain MR images with consistent longitudinal cortical thickness changes. Specifically, we utilize local intensity information to address the intensity inhomogeneity, spatial cortical thickness constraint to maintain the cortical thickness within a reasonable range, and temporal cortical thickness constraint to ensure the cortical thickness at the current time-point to be temporally consistent with thicknesses in the neighboring time-points. The proposed method has been tested on BLSA dataset and ADNI dataset. Both qualitative and quantitative experimental results demonstrate the accuracy and consistency of the proposed method, in comparison to other state-of-the-art 4D segmentation methods.