System and method for feature extraction and classification on ultrasound tomography images

A computer implemented method for characterizing a lesion in a volume of tissue, the method comprising:

• receiving a plurality of acoustic renderings, the acoustic renderings comprising a representation of sound propagation through the volume of tissue, wherein the plurality of acoustic renderings comprises at least a transmission rendering and a reflection rendering;
• determining a set of prognostic parameters, wherein the set of prognostic parameters comprises one or a plurality of sound propagation metrics that are derived from the plurality of acoustic renderings;
• and
• applying a classifier model to classify the volume of tissue, wherein the classifier model is generated from:
• a first classifier configured to assign each prognostic parameter of a plurality of prognostic parameters a predictive value and
• generate the set of prognostic parameters from the plurality of prognostic parameters based on the predictive value of each prognostic parameter of the plurality of prognostic parameters, wherein the first classifier configured to trim the plurality of prognostic parameters based on the predictive value to generate the set of prognostic parameters;
• and
• a second classifier configured to calculate a score relating to a probability that the lesion is of a classification based on the set of prognostic parameters, wherein said second classifier is a trained classifier trained at least in part on the set of prognostic parameters and a plurality of classified acoustic renderings.