US 12,254,623 B2
Artificial intelligence assisted diagnosis and classification of liver cancer from image data
Mélodie Sperandio, Paris (FR); Lorraine Jammes, Montrouge (FR); Marine Loth, Noisy-le-Roi (FR); Baptiste Perrin, Buc (FR); Mireille Haddad, Villejuif (FR); and Véronique Claire Jacqueline Ferry, Villeurbanne (FR)
Assigned to GE Precision Healthcare LLC, Waukesha, WI (US)
Filed by GE Precision Healthcare LLC, Milwaukee, WI (US)
Filed on Jul. 2, 2021, as Appl. No. 17/366,778.
Claims priority of provisional application 63/169,665, filed on Apr. 1, 2021.
Prior Publication US 2022/0318991 A1, Oct. 6, 2022
Int. Cl. G06T 7/00 (2017.01); G16H 30/40 (2018.01); G16H 50/20 (2018.01)
CPC G06T 7/0012 (2013.01) [G16H 30/40 (2018.01); G16H 50/20 (2018.01); G06T 2200/24 (2013.01); G06T 2207/30056 (2013.01); G06T 2207/30096 (2013.01)] 21 Claims
OG exemplary drawing
 
1. A system, comprising:
a memory that stores computer executable components; and
a processor that executes the computer executable components stored in the memory, wherein the computer executable components comprise:
a rendering component that facilitates rendering medical images of a liver of a patient in a graphical user interface of a medical imaging application that facilitates evaluating the medical images, wherein the rendering component associates different groups of the medical images in different windows of the graphical user interface, the different groups corresponding to different hepatic vascular phases;
a lesion detection component that identifies an observation on the liver as depicted in at least some of the medical images; and
a feature detection component that determines, based on application of one or more feature detection algorithms to the at least some of the medical images, whether each feature included in a defined set of features, is present or absent for the observation, wherein the one or more feature detection algorithms are configured to detect each feature in a subset of the different groups,
wherein the rendering component renders results of the feature detection component via the graphical user interface, wherein the results indicate whether each feature is present or absent for the observation, and
wherein based on a feature being indicated as present, the results comprise an interactive view button associated with the feature which in response to selection thereof, causes the rendering component to render a representative image of the at least some of the medical images comprising the feature in a window of the different windows corresponding to a group of the different groups to which the representative image belongs.