Segmentation of PET/SPECT images by using sensor-array-signal processing technique

A new signal processing method is developed for PET and SPECT image region detection and segmentation. The proposed technique formulates the region detection problem in a multidimensional signal processing framework such that a signal structure similar to sensor-array-processing signal presentation is created and the advanced sensor-array-signal processing techniques are employed. Following the region detection, the segmentation is completed by region parameter estimation and pixel classification. The developed method is an unsupervised, non-model-based, eigenstructure approach. It properly utilizes the spatial correlations among the pixels and eliminates the ad-hoc assumptions in image modeling. It possesses extensive computation speed superiority over existing model-based approaches. Details of this technique and several examples are presented