Google Inc.

Shahar Jamshy

Tushar Deepak Chandra

Tal Shaked

Jeremiah Harmsen

Krishnan Eswaran

Alexandre Tachard Passos

Heng-Tze Cheng

Shravya R Shetty

Daniel Shing Shun Tse

David Edgar Lluncor

Zvika Ben-Haim

A computer-implemented system is described for identifying and retrieving similar radiology images to a query image. The system includes one or more fetchers receiving the query image and retrieving a set of candidate similar radiology images from a data store. One or more scorers receive the query image and the set of candidate similar radiology images and generate a similarity score between the query image and each candidate image. A pooler receives the similarity scores from the one or more scorers, ranks the candidate images, and returns a list of the candidate images reflecting the ranking. The scorers implement a modelling technique to generate the similarity score capturing a plurality of similarity attributes of the query image and the set of candidate similar radiology images and annotations associated therewith. For example, the similarity attributes could be patient, diagnostic and/or visual similarity, and the modelling techniques could be triplet loss, classification loss, regression loss and object detection loss.

Similar image search for radiology

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training a factorization model to learning features of model inputs of a trained model such that the factorization model is predictive of outcome for which the machine learned model is trained.

Factorized models

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Santa Clara, CA, United States of America

Shahar Jamshy