3-D quantitative analysis of brain SPECT images

The main purpose of this work is to develop a computer-based technique for quantitative analysis of 3-D brain images obtained by single photon emission computed tomography (SPECT). In particular, the volume and location of ischemic lesion and penumbra is important for early diagnosis and treatment of infarcted regions of the brain. SPECT imaging is typically used as diagnostic tool to assess the size and location of the ischemic lesion. The segmentation method presented in this paper utilizes a 3-D deformable model in order to determine size and location of the regions of interest. The evolution of the model is computed using a level-set implementation of the algorithm. In addition to 3-D deformable, model the method utilizes edge detection and region growing for realization of a pre-processing. Initial experimental results have shown that the method is useful for SPECT image analysis.