US 12,451,235 B2
Systems and methods for automatically diagnosing X-ray images
Hamid Reza Tizhoosh, Rochester, MN (US); and Ho Yin Sze-To, Tuen Mun (HK)
Assigned to Hamid Reza Tizhoosh, Rochester, MN (US)
Filed by Hamid Reza Tizhoosh, Rochester, MN (US)
Filed on Nov. 3, 2022, as Appl. No. 17/980,064.
Application 17/980,064 is a continuation of application No. PCT/CA2021/050582, filed on Apr. 28, 2021.
Claims priority of provisional application 63/020,119, filed on May 5, 2020.
Claims priority of provisional application 63/154,078, filed on Feb. 26, 2021.
Prior Publication US 2023/0119642 A1, Apr. 20, 2023
Int. Cl. G16H 30/40 (2018.01); A61B 6/00 (2024.01); G06T 7/00 (2017.01); G06T 7/11 (2017.01); G06V 10/82 (2022.01); G16H 50/20 (2018.01)
CPC G16H 30/40 (2018.01) [A61B 6/5217 (2013.01); G06T 7/0014 (2013.01); G06T 7/11 (2017.01); G06V 10/82 (2022.01); G16H 50/20 (2018.01); G06T 2207/10116 (2013.01); G06T 2207/20021 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30061 (2013.01)] 24 Claims
OG exemplary drawing
 
1. A method for diagnosing a query X-ray image, the method comprising:
applying an artificial neural network model to the query X-ray image to extract a query feature vector representative of image characteristics of the query X-ray image, wherein applying the artificial neural network model to the query X-ray image comprises:
dividing the query X-ray image into one or more query image portions;
generating a value to represent the image characteristics within each query image portions of the one or more query image portions; and
generating the query feature vector to include the value for each query image portion;
comparing the query feature vector with one or more annotated feature vectors associated with respective one or more annotated X-ray images stored in an annotated image database to determine a similarity level between the query X-ray image and each annotated X-ray image of the one or more annotated X-ray images;
associating the query X-ray image with a set of annotated X-ray images based at least on the similarity level and a similarity threshold; and
assigning the query X-ray image with a disease classification based at least on the disease classification of one or more annotated X-ray images of the set of annotated X-ray images.