Techniques for automated classification of 1H-MRSI voxels of the human prostate to draw a radiologist's attention include receiving spectra for voxels from a scan of a human prostate, and segregating the voxels by anatomical zone of the prostate where voxels would be expected to have similar spectral signatures. In some embodiments, the whole prostate gland is a single zone. The spectrum of each voxel in the zone is provided as input to a neural network trained to give expert classification in the zone for a training set. Each voxel is automatically classified based on output from the neural network. In an alternative embodiment, the amplitudes are determined of principal components derived from all spectra in a training set in the zone. Those amplitudes are provided as input to a functional form fit to the expert classification. Each voxel is automatically classified based on output from the functional form.
MALIGNANT TISSUE RECOGNITION MODEL FOR THE PROSTATE