公开(公告)号：US12131525B2

公开(公告)日：2024-10-29

申请号：US17620142

申请日：2020-06-25

Applicant: KONINKLIJKE PHILIPS N.V.

Inventor： Alexandra Groth ,  Axel Saalbach ,  Ivo Matteo Baltruschat ,  Jens Von Berg ,  Michael Grass

IPC: G06V10/00 ,  G06T7/00 ,  G06V10/44 ,  G06V10/764 ,  G06V10/774 ,  G06V10/82 ,  G06V10/96 ,  G06V20/70

CPC classification number: G06V10/82 ,  G06T7/0012 ,  G06V10/454 ,  G06V10/764 ,  G06V10/774 ,  G06V10/96 ,  G06V20/70 ,  G06T2207/10081 ,  G06T2207/10124 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06V2201/03

Abstract: Multi-task deep learning method for a neural network for automatic pathology detection, comprising the steps: receiving first image data (I) for a first image recognition task; receiving (S2) second image data (V) for a second image recognition task; wherein the first image data (I) is of a first datatype and the second image data (V) is of a second datatype, different from the first datatype; determining (S3) first labeled image data (IL) by labeling the first image data (I) and determining second synthesized labeled image data (ISL) by synthesizing and labeling the second image data (V); training (S4) the neural network based on the received first image data (I), the received second image data (V), the determined first labeled image data (IL) and the determined second labeled synthesized image data (ISL); wherein the first image recognition task and the second image recognition task relate to a same anatomic region where the respective image data is taken from and/or relate to a same pathology to be recognized in the respective image data.