	US 12,327,356 B2
	Methods of assessing lung disease in chest X-rays
Richard Vlasimsky, Denver, CO (US)
Assigned to IMIDEX, INC., Denver, CO (US)
Filed by IMIDEX, INC., Denver, CO (US)
Filed on Jun. 26, 2024, as Appl. No. 18/754,934.
Application 18/754,934 is a continuation of application No. 17/545,383, filed on Dec. 8, 2021, granted, now 12,039,724.
Claims priority of provisional application 63/123,183, filed on Dec. 9, 2020.
Prior Publication US 2024/0346654 A1, Oct. 17, 2024
Int. Cl. G06T 7/00 (2017.01); A61B 6/00 (2006.01); A61B 6/50 (2024.01); G06N 3/045 (2023.01); G06T 3/40 (2006.01); G06T 7/11 (2017.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01); G16H 30/40 (2018.01); G16H 50/20 (2018.01)

CPC G06T 7/0012 (2013.01) [A61B 6/50 (2013.01); A61B 6/5217 (2013.01); G06N 3/045 (2023.01); G06T 3/40 (2013.01); G06T 7/11 (2017.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01); G16H 30/40 (2018.01); G16H 50/20 (2018.01); G06T 2207/10116 (2013.01); G06T 2207/20076 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30061 (2013.01); G06T 2207/30096 (2013.01); G06T 2207/30168 (2013.01); G06V 2201/032 (2022.01)]

12 Claims

1. A diagnostic method, the method comprising: providing an image file of a chest x-ray from a patient to a machine learning system that has been trained on training data only available at a plurality of sources separated by time and/or geography and the training comprises connecting the machine learning system to the plurality of sources at different times and/or locations, wherein the machine learning system operates by resizing the image file of the chest x-ray into a first image that depicts the entire x-ray at a reduced resolution and placing a subsection of the file into a second image at an original resolution; analyzing the first and second images in parallel by respective first and second neural networks to output scores indicating a probability of a nodule, wherein the machine learning system has been trained to learn associations between features in chest x-rays and known pathology results with an area under the curve (AUC) of true positives over false positives for learned feature associations is between 0.7 and 0.83; and operating the machine learning system to detect lung nodules.