公开(公告)号：US11126649B2

公开(公告)日：2021-09-21

申请号：US16032276

申请日：2018-07-11

Applicant: Google LLC

Inventor： Krishnan Eswaran ,  Shravya Shetty ,  Daniel Shing Shun Tse ,  Shahar Jamshy ,  Zvika Ben-Haim

IPC: G06F17/00 ,  G06F7/00 ,  G06F16/432 ,  G16H30/40 ,  G16H30/20 ,  G06K9/62 ,  G06T7/00 ,  G06F17/18

Abstract: 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.

公开(公告)号：US20200019617A1

公开(公告)日：2020-01-16

申请号：US16032276

申请日：2018-07-11

Applicant: Google LLC

Inventor： Krishnan Eswaran ,  Shravya Shetty ,  Daniel Shing Shun Tse ,  Shahar Jamshy ,  Zvika Ben-Haim

IPC: G06F17/30 ,  G16H30/40 ,  G16H30/20 ,  G06K9/62 ,  G06F17/18 ,  G06T7/00

Abstract: 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.