US 12,446,842 B2
System and method for hierarchical multi-level feature image synthesis and representation
Haili Chui, Fremont, CA (US); Liyang Wei, San Jose, CA (US); Jun Ge, Cupertino, CA (US); Xiangwei Zhang, Fremont, CA (US); and Nikolaos Gkanatsios, Newtown, CT (US)
Assigned to Hologic, Inc., Marlborough, MA (US)
Filed by Hologic, Inc., Marlborough, MA (US)
Filed on Feb. 28, 2024, as Appl. No. 18/590,033.
Application 18/590,033 is a continuation of application No. 17/692,989, filed on Mar. 11, 2022, granted, now 11,957,497.
Application 17/692,989 is a continuation of application No. 16/497,764, granted, now 11,399,790, issued on Aug. 2, 2022, previously published as PCT/US2018/024911, filed on Mar. 28, 2018.
Claims priority of provisional application 62/478,977, filed on Mar. 30, 2017.
Prior Publication US 2024/0315654 A1, Sep. 26, 2024
Int. Cl. A61B 6/50 (2024.01); A61B 6/00 (2024.01); A61B 6/02 (2006.01); G06F 18/25 (2023.01); G06K 9/00 (2022.01); G06T 7/00 (2017.01); G06T 17/10 (2006.01); G06V 10/80 (2022.01); G06V 30/24 (2022.01)
CPC A61B 6/502 (2013.01) [A61B 6/025 (2013.01); G06F 18/254 (2023.01); G06T 7/0012 (2013.01); G06T 17/10 (2013.01); G06V 10/806 (2022.01); G06V 10/809 (2022.01); G06V 30/2504 (2022.01); G06T 2207/30068 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method for processing breast tissue image data, comprising:
providing a set of image slices that collectively depict at least a portion of a patient's breast tissue, wherein the set of image slices are generated by one of a tomosynthesis acquisition system and a combination tomosynthesis/mammography system;
processing the set of image slices using a first-level feature module to detect at least one first assigned feature of a high-dimensional object present in the patient's breast tissue;
generating a first-level feature map based on the at least one first assigned feature;
processing the set of image slices using a second-level feature module to detect at least one second assigned feature of the high-dimensional object present in the patient's breast tissue,
wherein the at least one first assigned feature is a different level feature than the at least one second assigned feature;
generating a second-level feature map based on the at least one second assigned feature;
and
combining the first-level feature map and the second-level feature map into an object map that indicates a probability region of the high-dimensional object in each image slice.