Patent ID: 11963788
Assignee: CITY UNIVERSITY OF HONG KONG
Field: Medical technology (Instruments)
Classification: CPC A  G | IPC A  G

Claim 15:
16. A method for using a graph-based prostate diagnosis network to predict a prostate health status of a patient from a 3D magnetic resonance imaging (MRI) scan containing a plurality of 2D MRI slices, the method comprising:
an instance embedding extraction stage including extracting, by a feature extractor, a plurality of preliminary instance embeddings Z corresponding to the plurality of 2D MRI slices X respectively;
a preliminary diagnosis stage including:
aggregating, by a pooling operator, the plurality of preliminary instance embeddings Z together to generate a preliminary bag embedding zbag; and
calculating, by a preliminary classifier, an instance importance parameter w based on the preliminary bag embedding zbag;

an instance importance calculation stage including calculating, by an instance importance calculator, a plurality of instance importances a corresponding to the plurality of preliminary instance embeddings respectively based on the instance importance parameter w; and
a refined diagnosis stage including:
generating, by a plurality of importance-guided graph (IGraph) layers, a plurality of improved instance embeddings {tilde over (Z)} by performing a plurality of graph convolutions on the plurality of preliminary instance embeddings Z in a sequential manner;
generating, by an embedding aggregator, an improved bag embedding zI by aggregating the plurality of improved instance embeddings {tilde over (Z)} with the plurality of instance importances a; and
processing, by a refined classifier, the improved bag embedding zI to generate a refined diagnosis prediction y for predicting prostate health status of the patient.