Segmentation and feature extraction techniques, with applications to MRI head studies.
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.
Ashton
E A
EA
Department of Electrical Engineering, University of Rochester, NY 14627, USA.
Berg
M J
MJ
Parker
K J
KJ
Weisberg
J
J
Chen
C W
CW
Ketonen
L
L
D000465:Algorithms; D001499:Bayes Theorem; D001921:Brain / Q000033:anatomy & histology; D003198:Computer Simulation; D006257:Head / Q000033:anatomy & histology*; D006624:Hippocampus / Q000033:anatomy & histology; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging / Q000379:methods*; D015203:Reproducibility of Results