A Computational Approach to Resolve Cell Level Mechanisms of Early Glandular Epithelial Cancer Progression

ISEA morphology index (M = E + D + S) was created in part to facilitate and automate morphology analysis, an essential aspect of our study, which otherwise would have required manual, visual screening of simulation images following changes to analogue implementation or parameterization. Conceptual parallels can be drawn between the morphology index and automated methods of classifying tumor histology. For automated tumor grading, various methods of image processing along with correlation-based techniques have been devised to grade histological images. Included are hybrid segmentation methods [1] that quantify morphological features into numerical scores. Similar to those methods, the morphology index provides a numeric scale to classify multi-aspect features of ISEA morphology at the conclusion of each simulation.