Segmentation and Feature Extraction Techniques, with Applications to MRI Head Studies

Abstract

To obtain a three-dimensional reconstruction of the hippocampus from a volumetric MRI head study, it is necessary to separate that structure not only from the surrounding white matter, but also from contiguous areas of gray matter--the amygdala and cerebral cortex. At present it is necessary for a physician to manually segment the hippocampus on each slice of the volume to obtain such a reconstruction. This process is time consuming, and is subject to inter- and intraoperator variation as well as large discontinuities between slices. We propose a novel technique, making use of a combination of gray scale and edge-detection algorithms and some a priori knowledge, by which a computer may make an unsupervised identification of a given structure through a series of contiguous images. This technique is applicable even if the structure includes so-called false contours or missing contours. Applications include three-dimensional reconstruction of difficult-to-segment regions of the brain, and volumetric measurements of structures from series of two-dimensional images.