Yu Lucy Zhao

US Patent:

20230005136, Jan 5, 2023

Filed:

Jun 9, 2022

Appl. No.:

17/806156

Inventors:

- Erlangen, DE
Gerardo Hermosillo Valadez - West Chester PA, US
Yoshihisa Shinagawa - Downingtown PA, US
Matthias Wolf - Coatesville PA, US
Anna Jerebko - Paoli PA, US
Yu Zhao - West Chester PA, US
Katharina Schmidler Burk - Cedar City UT, US
Mahesh Ranganath - Malvern PA, US

International Classification:

G06T 7/00
A61B 5/055

Abstract:

A computer implemented method and apparatus for determining a location at which a given feature is represented in medical imaging data is disclosed. A first descriptor for a first location in first medical imaging data is obtained. The first location is the location within the first medical imaging data at which the given feature is represented. A second descriptor for each of a plurality of candidate second locations in second medical imaging data is obtained. A similarity metric indicating a degree of similarity with the first descriptor is calculated for each of the plurality of candidate second locations. A candidate second location is selected from among the plurality of candidate second locations based on the calculated similarity metrics. The location at which the given feature is represented in the second medical imaging data is determined based on the selected candidate second location.

US Patent:

20210287363, Sep 16, 2021

Filed:

Mar 3, 2021

Appl. No.:

17/190674

Inventors:

- Erlangen, DE
Yimo GUO - Chester Springs PA, US
Gerardo HERMOSILLO VALADEZ - West Chester PA, US
Zhigang PENG - Ambler PA, US
Yu ZHAO - Athens GA, US

Assignee:

Siemens Healthcare GmbH - Erlangen

International Classification:

G06T 7/00
G06T 3/60
G06T 7/70
A61B 90/00

Abstract:

Disclosed is a computer-implemented method for detecting one or more anatomic landmarks in medical image data. In an embodiment, the method includes receiving a medical image data set depicting a body part of a patient; and determining a first set of anatomic landmarks from a first representation of the medical image data set at a first resolution by applying a first trained function to the first representation of the medical image data set. Based on that, a second set of anatomic landmarks is determined from a second representation of the medical image data set at a second resolution, the second resolution being higher than the first resolution, by applying a second trained function different than the first trained function to the second representation of the medical image data set and using the first set of landmarks by the second trained function.