1. A method for performing multi-stage classification for detection of cancer regions from one or more digitized images of biopsy slides comprising: pre-processing, from the digitized images, biopsy regions of interest or biopsy whole-slides, using color normalization methods and segmentation methods; decomposing the pre-processed digitized images into several segments; describing the image segments by forming feature vectors based on at least one of textural, color, or morphology tissue characteristics; classifying the image segments using one or more classification methods in a first classification stage, wherein the classification methods utilize the feature vectors of the image segments, and further wherein the classification methods are able to produce scores and posterior conditional probabilities or equivalents for each possible class, and further wherein the first classification stage is a multi-class classifier; classifying one or more of the image segments using a second classification stage if one or more conditions are met, wherein the second classification stage comprises a set of one or more specialized classifiers or refinement classifiers which are trained on a smaller group of classes with respect to the classifiers used in the first stage; classifying, based upon either the first or second classification stage, a portion of the region of interest or biopsy whole slides, as cancerous or non-cancerous; determining a cancer classification, tumor extent, tumor size, or tumor localization based at least in part upon the output of either of the first or second classification stage.