10. An image processing system configured to process a medical image data set for a patient, comprising: a memory configured to store a medical image data set; and a processor configured to apply a first classifier to the medical image data set, the first classifier having a sensitivity configured to identify a first subset of the medical image data set with one or more characteristics similar to a plaque region and configured to pass the identified subset to a second classifier and to apply the second classifier to the first subset the second classifier having a specificity configured to confirm the presence, or absence, of the plaque region in one or more portions of the first subset, wherein the plaque region is selected from an occlusive plague region and a vulnerable plague region, and wherein each of the first classifier and the second classifier uses a Bayesian classification methodology, k-nearest neighbor classification methodology, neural network classification methodology, or any combination thereof, the processor further configured to apply a third classifier to the medical image data set, the third classifier having a sensitivity configured to identify a second subset of the medical image data set with one or more characteristics similar to a second specified distinctive region, pass the identified second subset to a fourth classifier and further apply the fourth classifier to the second subset, the fourth classifier having a specificity configured to confirm the presence, or absence, of the second specified distinctive region, wherein each of the third classifier and the fourth classifier uses a Bayesian classification methodology, k-nearest neighbor classification methodology, neural network classification methodology, or any combination thereof, wherein the second specified distinctive region is a different type of region than the plaque region.
10. An image processing system configured to process a medical image data set for a patient, comprising: a memory configured to store a medical image data set; and a processor configured to apply a first classifier to the medical image data set, the first classifier having a sensitivity configured to identify a first subset of the medical image data set with one or more characteristics similar to a plaque region and configured to pass the identified subset to a second classifier and to apply the second classifier to the first subset the second classifier having a specificity configured to confirm the presence, or absence, of the plaque region in one or more portions of the first subset, wherein the plaque region is selected from an occlusive plague region and a vulnerable plague region, and wherein each of the first classifier and the second classifier uses a Bayesian classification methodology, k-nearest neighbor classification methodology, neural network classification methodology, or any combination thereof, the processor further configured to apply a third classifier to the medical image data set, the third classifier having a sensitivity configured to identify a second subset of the medical image data set with one or more characteristics similar to a second specified distinctive region, pass the identified second subset to a fourth classifier and further apply the fourth classifier to the second subset, the fourth classifier having a specificity configured to confirm the presence, or absence, of the second specified distinctive region, wherein each of the third classifier and the fourth classifier uses a Bayesian classification methodology, k-nearest neighbor classification methodology, neural network classification methodology, or any combination thereof, wherein the second specified distinctive region is a different type of region than the plaque region. 11. The image processing system of claim 10 , wherein the sensitivity of the first classifier is relatively higher than the sensitivity of the second classifier and the specificity of the second classifier is relatively higher than the specificity of the first classifier.