Patent ID: 11886975
Assignee: THE JOHNS HOPKINS UNIVERSITY
Field: Computer technology (Electrical engineering)
Classification: CPC G  A | IPC G

Claim 6:
7. A method of generating a model to predict prospective pathology scores of test subjects having a pathology, the method comprising:
extracting a first plurality of image features from sets of longitudinal single photon emission computed tomography (SPECT) and/or positron emission tomography (PET) images obtained from a plurality of reference subjects having the pathology, wherein the images features extracted from at least first and second sets of the longitudinal SPECT and/or PET images are extracted separate from one another to produce a first feature vector;
extracting a second plurality of image features from the sets of the longitudinal SPECT and/or PET images when the longitudinal SPECT and/or PET images are in an unprocessed form to produce a second feature vector;
extracting a plurality of clinical features from clinical data obtained from the plurality of reference subjects having the pathology, which clinical features comprise pathology sub-scores to produce a third feature vector; and,
training one or more layers of an artificial neural network (ANN) using the first, second, and third feature vectors, thereby generating the model to predict prospective pathology scores of test subjects having the pathology.