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

Claim 0:
1. 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 directly 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 image 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 maximum intensity projections (MIPs) of the sets of the longitudinal SPECT and/or PET images to produce a second feature vector;
extracting a third plurality of image features from semi-quantitative imaging measures of the sets of the longitudinal SPECT and/or PET images to produce a third feature vector;
extracting a plurality of non-imaging features from non-imaging data obtained from the plurality of reference subjects having the pathology to produce a fourth feature vector; and,
training multiple artificial neural networks (ANNs) using the first, second, third, and fourth feature vectors and a plurality of clinical features from clinical data obtained from the plurality of reference subjects having the pathology to produce an ensemble of ANNs, thereby generating the model to predict prospective pathology scores of test subjects having the pathology.