Patent ID: 11893811
Assignee: CARNEGIE MELLON UNIVERSITY
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. A method comprising:
obtaining a high-resolution whole slide image of a post-birth placenta;
analyzing the whole slide image, using a trained machine learning model, to identify one or more blood vessels in the placenta, the analysis occurring at a lower resolution than the native resolution of the whole slide image;
classifying the identified blood vessels at a higher resolution using a trained machine learning classifier that outputs a latent vector for each classified blood vessel:
aggregating the latent vectors for a predetermined number of classified blood vessels;
pooling the aggregated latent vectors by calculating a maximum or minimum of the data for each node of a feature map of the machine learning classifier;
reducing the dimension on the pooled aggregated latent vectors to produce a reduced dimension latent vector; and
performing a binary classification for each whole slide image based on the latent vector.