Methods and apparatus associated with distinguishing invasive adenocarcinoma (IA) from in situ adenocarcinoma (AIS) are described. One example apparatus includes a set of logics, and a data store that stores three dimensional (3D) radiological images of tissue demonstrating IA or AIS. The set of logics includes a classification logic that generates an invasiveness classification for a diagnostic 3D radiological image, a training logic that trains the classification logic to identify a texture feature associated with IA, an image acquisition logic that acquires a diagnostic 3D radiological image of a region of tissue demonstrating cancerous pathology and that provides the diagnostic 3D radiological image to the classification logic, and a prediction logic that generates an invasiveness score based on the diagnostic 3D radiological image and the invasiveness classification. The training logic trains the classification logic using a set of 3D histological reconstructions combined with the set of 3D radiological images.
Disease characterization from fused pathology and radiology data