Patent ID: 8295575
Filing Date: 2012-10-23
Classification: G06K,G06T

Abstract:
1. A method of constructing a classifier to detect cancer sub-clusters in an organ using a dataset containing in vivo high resolution magnetic resonance imaging (MRI) data, comprising the steps of: a. preprocessing the MRI data by correcting bias field inhomogeneity and non-linear MRI artifacts to create a corrected MRI scene; b. rigidly or non-rigidly registering determined correspondences of whole-mount histological sections (WMHS) and MRI data via a Combined Feature Ensemble Mutual Information (COFEMI) technique, thereby obtaining cancerous and non-cancerous regions in the preprocessed MRI data; c. extracting features on a per-voxel basis from the MRI scene; d. embedding the extracted feature into a low dimensional Eigen space using manifold learning techniques on a per-voxel basis, thereby non-linearly reducing the dimensionality of the extracted image features; e. training a classifier on the reduced dimensional Eigen feature to discriminate a voxel from an MRI scene as cancerous or normal; and f. classifying each voxel in the MRI scene based on its reduced dimensional Eigen feature as cancerous or normal, thereby detecting cancer.