Semi-automatic brain morphometry in CT

Presents development and application of a semi-automatic method for estimating volumes of brain tissues from computed tomography (CT) images. The method does not require manual drawing of tissue boundaries. The steps of the new method are: (1) intracranial brain volume is segmented from skull and background using thresholding and morphological operations; (2) noise is suppressed using a nonlinear edge-preserving filter; (3) a histogram of the resulting image is generated and the dominant peak is removed; (4) minima and maxims of the histogram are identified and the brain is segmented into normal tissues, cerebrospinal fluid, and lesions, if present; (5) previous steps are repeated for each slice and volume of each tissue is estimated from the results. The method has shown to be faster and more reproducible than conventional methods. Details and significance of each step of the method are explained. Experimental results using a simulation, a phantom, and selected clinical cases are presented