US 12,334,224 B2
Cardiovascular assessment of patients suspected of having COVID-19
Puneet Sharma, Princeton Junction, NJ (US); Saikiran Rapaka, Pennington, NJ (US); and Ingo Schmuecking, Yardley, PA (US)
Assigned to Siemens Healthineers AG, Forchheim (DE)
Filed by Siemens Healthineers AG, Forchheim (DE)
Filed on May 19, 2020, as Appl. No. 16/877,646.
Claims priority of provisional application 63/009,517, filed on Apr. 14, 2020.
Prior Publication US 2021/0319900 A1, Oct. 14, 2021
Int. Cl. G16H 50/30 (2018.01); A61B 5/00 (2006.01); A61B 5/0205 (2006.01); G16H 10/60 (2018.01); G16H 50/20 (2018.01); G16H 50/50 (2018.01); G06T 7/00 (2017.01)
CPC G16H 50/30 (2018.01) [A61B 5/0205 (2013.01); A61B 5/4842 (2013.01); G16H 10/60 (2018.01); G16H 50/20 (2018.01); G16H 50/50 (2018.01); G06T 7/0012 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30061 (2013.01)] 18 Claims
OG exemplary drawing
 
1. A computer implemented method comprising:
receiving patient data of a patient, the patient data comprising one or more input medical images of a chest of the patient, one or more metrics quantifying abnormality patterns of a lung disease in lungs of the patient determined based on the one or more input medical images, and results of cardiovascular imaging exams; and
computing a combination metric representing an assessment of cardiovascular disease of the patient and an assessment of lung disease of the patient using a trained machine learning based network, the trained machine learning based network computing the combination metric based on the one or more input medical images of the chest of the patient, the one or more metrics quantifying the abnormality patterns of the lung disease in the lungs of the patient, and the results of the cardiovascular imaging exams.