US 12,293,822 B2
Automatic assay assessment and normalization for image processing
Yao Nie, Sunnyvale, CA (US); and Maria V. Sainz De Cea, Chicago, IL (US)
Assigned to VENTANA MEDICAL SYSTEMS, INC., Tucson, AZ (US)
Filed by Ventana Medical Systems, Inc., Tucson, AZ (US)
Filed on Apr. 2, 2024, as Appl. No. 18/625,118.
Application 18/625,118 is a continuation of application No. 18/326,716, filed on May 31, 2023, granted, now 11,990,228.
Application 18/326,716 is a continuation of application No. 17/827,656, filed on May 27, 2022, granted, now 11,715,557, issued on Aug. 1, 2023.
Application 17/827,656 is a continuation of application No. 16/777,649, filed on Jan. 30, 2020, granted, now 11,380,085, issued on Jul. 5, 2022.
Application 16/777,649 is a continuation of application No. PCT/EP2018/070978, filed on Aug. 2, 2018.
Claims priority of provisional application 62/541,621, filed on Aug. 4, 2017.
Prior Publication US 2024/0266035 A1, Aug. 8, 2024
This patent is subject to a terminal disclaimer.
Int. Cl. G06T 3/40 (2024.01); G01N 15/1433 (2024.01); G06F 16/535 (2019.01); G06F 18/214 (2023.01); G06V 20/69 (2022.01); G16H 10/40 (2018.01); G16H 30/40 (2018.01); G16H 50/20 (2018.01); G16H 70/60 (2018.01); G01N 15/10 (2006.01)
CPC G16H 30/40 (2018.01) [G01N 15/1433 (2024.01); G06F 16/535 (2019.01); G06F 18/214 (2023.01); G06T 3/40 (2013.01); G06V 20/698 (2022.01); G16H 10/40 (2018.01); G16H 50/20 (2018.01); G16H 70/60 (2018.01); G01N 2015/1006 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method comprising:
determining an estimated titer level of a query image, the query image being an image of a biological sample stained with a stain, wherein the estimated titer level of the query image is determined in-part by classifying stain image features derived from image patches of the query image; and
normalizing a titer level of the query image, wherein the titer level of the query image is normalized by:
deriving chromatic distribution coordinates and density distribution coordinates in the query image within a color model which incorporates density information;
aligning, based in-part on a first parameter value associated with the estimated titer level of the query image, the chromatic distributions coordinates in the query image with template image chromatic distribution coordinates to provide transformed chromatic distribution coordinates;
scaling, based in-part on a second parameter value associated with the estimate titer level of the query image, the density distribution coordinates in the query image with template image density distribution coordinates to provide transformed density distribution coordinates; and
reconstructing an RGB image by inversely transforming the query image within the color model incorporating the density information using weighted transformed chromatic distribution coordinates and weighted transformed density distribution coordinates.