Mathematical Morphology Techniques For Image Processing Applications In Biomedical Imaging
GRACE T. BARTOO, Yongmin Kim, Robert M. Haralick, David Nochlin, S. M. Sumi · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1988
Mathematical morphology operations allow object identification based on shape and are useful for grouping a cluster of small objects into one object. Because of these capabilities, we have implemented and evaluated this technique for our study of Alzheimer's disease. The microscopic hallmark of Alzheimer's disease is the presence of brain lesions known as neurofibrillary tangles and senile plaques. These lesions have distinct shapes compared to normal brain tissue. Neurofibrillary tangles appear as flame-shaped structures, whereas senile plaques appear as circular clusters of small objects. In order to quantitatively analyze the distribution of these lesions, we have developed and applied the tools of mathematical morphology on the Pixar Image Computer. As a preliminary test of the accuracy of the automatic detection algorithm, a study comparing computer and human detection of senile plaques was performed by evaluating 50 images from 5 different patients. The results of this comparison demonstrates that the computer counts correlate very well with the human counts (correlation coefficient = .81). Now that the basic algorithm has been shown to work, optimization of the software will be performed to improve its speed. Also future improvements such as local adaptive thresholding will be made to the image analysis routine to further improve the systems accuracy.