US 12,462,391 B2
Patient-specific auto-segmentation in online adaptive radiotherapy
Simeng Zhu, Troy, MI (US); and Supratik Bose, San Ramon, CA (US)
Assigned to Siemens Healthineers International AG, Steinhausen (CH)
Filed by Siemens Healthineers International AG, Steinhausen (CH)
Filed on Nov. 18, 2022, as Appl. No. 17/990,105.
Prior Publication US 2024/0169543 A1, May 23, 2024
Int. Cl. G06T 7/11 (2017.01); A61N 5/10 (2006.01)
CPC G06T 7/11 (2017.01) [A61N 5/1039 (2013.01); G06T 2200/24 (2013.01); G06T 2207/10081 (2013.01); G06T 2207/10088 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20092 (2013.01); G06T 2207/30004 (2013.01)] 18 Claims
OG exemplary drawing
 
1. A method, comprising:
executing, by one or more processors coupled to a non-transitory memory, a first segmentation model that receives a medical image of a patient as an input and generates an initial segmentation of the medical image for a radiotherapy treatment of the patient;
identifying, by the one or more processors, a refinement to the initial segmentation generated in response to an input at a user interface presenting the initial segmentation;
executing, by the one or more processors, a second segmentation model that receives the medical image, the initial segmentation of the medical image, and the refinement as input and generates a refined segmentation of the medical image;
identifying, by the one or more processors, a correction to the refined segmentation of the medical image;
fine-tuning, by the one or more processors, the first segmentation model for the patient based on the medical image and the correction to the refined segmentation to generate a first fine-tuned segmentation model; and
fine-tuning, by the one or more processors, the second segmentation model for the patient based on the medical image, the initial segmentation, and the correction to the refined segmentation to generate a second fine-tuned segmentation model.