US 11,694,331 B2
Capture and storage of magnified images
Parijat P. Prabhudesai, Goa (IN); Ganesh Kumar Mohanur Raghunathan, Bangalore (IN); Aditya Sista, Bangalore (IN); Sumit Kumar Jha, Jharkhand (IN); and Narasimha Murthy Chandan, Bangalore (IN)
Assigned to Applied Materials, Inc., Santa Clara, CA (US)
Filed by Applied Materials, Inc., Santa Clara, CA (US)
Filed on Jan. 7, 2022, as Appl. No. 17/571,427.
Application 17/571,427 is a continuation of application No. 16/746,569, filed on Jan. 17, 2020, granted, now 11,232,561.
Claims priority of provisional application 62/795,467, filed on Jan. 22, 2019.
Prior Publication US 2022/0164952 A1, May 26, 2022
This patent is subject to a terminal disclaimer.
Int. Cl. G06T 7/00 (2017.01); G06T 7/143 (2017.01); G06T 7/11 (2017.01)
CPC G06T 7/0012 (2013.01) [G06T 7/11 (2017.01); G06T 7/143 (2017.01); G06T 2207/30024 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method performed by one or more data processing apparatus which comprises, for each magnification level in a sequence of increasing magnification levels:
imaging one or more regions of interest at the current magnification level, comprising, for each region of interest:
obtaining a magnified image of the region of interest at the current magnification level; and
generating data defining one or more refined regions of interest based on the magnified image of the region of interest at the current magnification level, comprising:
processing the magnified image of the region of interest at the current magnification level using a detection machine learning model associated with the current magnification level to generate the data defining the one or more refined regions of interest,
wherein the detection machine learning model associated with the current magnification level is specialized to process magnified images at the current magnification level as a result of being trained on a set of training examples that includes magnified images at the associated magnification level;
wherein each refined region of interest corresponds to a proper subset of the region of interest, and
wherein the refined regions of interest provide the regions of interest to be imaged at a next magnification level from the sequence of increasing magnification levels.