公开(公告)号：US20230298136A1

公开(公告)日：2023-09-21

申请号：US17654864

申请日：2022-03-15

Applicant: GE Precision Healthcare LLC

Inventor： Bipul Das ,  Rakesh Mullick ,  Deepa Anand ,  Sandeep Dutta ,  Uday Damodar Patil ,  Maud Bonnard

IPC: G06T3/60 ,  G06T7/73 ,  G06V10/82 ,  G06V10/774 ,  G16H50/20

CPC classification number: G06T3/60 ,  G06T7/73 ,  G06V10/82 ,  G06V10/774 ,  G16H50/20 ,  G06T2200/04 ,  G06V2201/031 ,  G06T2207/20084 ,  G06T2207/20081

Abstract: Systems/techniques that facilitate deep learning multi-planar reformatting of medical images are provided. In various embodiments, a system can access a three-dimensional medical image. In various aspects, the system can localize, via execution of a machine learning model, a set of landmarks depicted in the three-dimensional medical image, a set of principal anatomical planes depicted in the three-dimensional medical image, and a set of organs depicted in the three-dimensional medical image. In various instances, the system can determine an anatomical orientation exhibited by the three-dimensional medical image, based on the set of landmarks, the set of principal anatomical planes, or the set of organs. In various cases, the system can rotate the three-dimensional medical image, such that the anatomical orientation now matches a predetermined anatomical orientation.

公开(公告)号：US20210312674A1

公开(公告)日：2021-10-07

申请号：US16899835

申请日：2020-06-12

Applicant: GE Precision Healthcare LLC

Inventor： Sidharth Abrol ,  Bipul Das ,  Sandeep Dutta ,  Saad A. Sirohey

IPC: G06T11/00 ,  G06T7/10 ,  G06N20/00 ,  G06K9/62

Abstract: Techniques are described for domain adaptation of image processing models using post-processing model correction According to an embodiment, a method comprises training, by a system operatively coupled to a processor, a post-processing model to correct an image-based inference output of a source image processing model that results from application of the source image processing model to a target image from a target domain that differs from a source domain, wherein the source image processing model was trained on source images from the source domain. In one or more implementations, the source imaging processing model comprises an organ segmentation model and the post-processing model can comprise a shape-autoencoder. The method further comprises applying, by the system, the source image processing model and the post-processing model to target images from the target domain to generate optimized image-based inference outputs for the target images.