Classification of medical images using context dependent methods

Ted R. Jackson; James R. Brookeman; Michael B. Merickel

doi:10.1117/12.154529

14 September 1993 Classification of medical images using context dependent methods

Ted R. Jackson, James R. Brookeman, Michael B. Merickel

Proceedings Volume 1898, Medical Imaging 1993: Image Processing; (1993) https://doi.org/10.1117/12.154529
Event: Medical Imaging 1993, 1993, Newport Beach, CA, United States

Abstract

We are developing a method to automatically classify multispectral medical images using context dependent methods. The model is built with the knowledge that cluster of tissue features will overlap in feature space. The goal is to reduce the classification error that results from this cluster overlap. Initialization of the probability of a pixel belonging to a tissue class can take advantage of a priori class distributions if such knowledge exists. Otherwise, the procedure can resort to modeling each class with a Gaussian distribution. These probabilities can then be iteratively updated using either a relaxation labeling algorithm or a Markov random fields algorithm. Once the model converges, iterations cease and each pixel is classified using the maximum probability for all classes.

Citation Download Citation

Ted R. Jackson, James R. Brookeman, and Michael B. Merickel "Classification of medical images using context dependent methods", Proc. SPIE 1898, Medical Imaging 1993: Image Processing, (14 September 1993); https://doi.org/10.1117/12.154529

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