US 12,268,498 B2
Systems and methods for quantitative diagnosis of anemia
Robert Mannino, Atlanta, GA (US); Wilbur Lam, Atlanta, GA (US); Gari Clifford, Atlanta, GA (US); and Erika Tyburski, Norcross, GA (US)
Assigned to EMORY UNIVERSITY, Atlanta, GA (US); CHILDREN'S HEALTHCARE OF ATLANTA, INC., Atlanta, GA (US); GEORGIA TECH RESEARCH CORPORATION, INC., Peachtree Corners, GA (US); and Sanguina, Inc., Peachtree Corners, GA (US)
Appl. No. 17/291,215
Filed by EMORY UNIVERSITY, Atlanta, GA (US); CHILDREN'S HEALTHCARE OF ATLANTA, INC., Atlanta, GA (US); GEORGIA TECH RESEARCH CORPORATION, INC., Atlanta, GA (US); and Sanguina, Inc, Peachtree Corners, GA (US)
PCT Filed Nov. 5, 2019, PCT No. PCT/US2019/059742
§ 371(c)(1), (2) Date May 4, 2021,
PCT Pub. No. WO2020/096999, PCT Pub. Date May 14, 2020.
Claims priority of provisional application 62/755,930, filed on Nov. 5, 2018.
Prior Publication US 2021/0361195 A1, Nov. 25, 2021
Int. Cl. A61B 5/00 (2006.01); A61B 5/103 (2006.01); A61B 5/145 (2006.01); A61B 5/1455 (2006.01); G06T 7/11 (2017.01); G06T 7/90 (2017.01); H04N 23/74 (2023.01)
CPC A61B 5/1455 (2013.01) [A61B 5/1032 (2013.01); A61B 5/14535 (2013.01); A61B 5/449 (2013.01); A61B 5/6898 (2013.01); A61B 5/7435 (2013.01); A61B 5/748 (2013.01); G06T 7/11 (2017.01); G06T 7/90 (2017.01); H04N 23/74 (2023.01); A61B 2560/0223 (2013.01); A61B 2576/02 (2013.01); G06T 2200/24 (2013.01); G06T 2207/10152 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/30104 (2013.01)] 19 Claims
OG exemplary drawing
 
1. A system for analyzing an image for estimating hemoglobin levels, the system comprising at least one processor configured to:
access a camera of a mobile device;
force on a flash functionality of the camera to normalize variable background lighting conditions;
capture, via the camera, an image of one or more fingernail beds of a user with the flash on, wherein:
the camera automatically uses at least one lighting condition setting; and
the mobile device automatically associates metadata with the image, the metadata comprising information about the flash and the at least one lighting condition setting;
receive the image from the camera;
receive an indication of one or more regions of interest on the image based, at least in part, on a user input to the mobile device, the one or more regions of interest at least partially including the one or more fingernail beds;
determine pixel intensity for each of the one or more regions of interest;
average pixel intensity from color channels across each of the one or more regions of interest;
transform the average pixel intensity from the color channels into a value that correlates with the user's approximate hemoglobin (Hgb) level using machine learning to correct for variations in the average pixel intensity;
adjust the value based on the metadata associated with the image to compensate for the at least one lighting condition setting and the flash;
determine the user's approximate Hbg level from the image based on the adjusted value;
and output the user's approximate Hgb level to a display of the mobile device, wherein the Hgb level is used to monitor changes to the user's Hgb levels over time.