Assessment of abnormality regions associated with a disease from chest ct images

Abstract

The present invention provides systems and methods for assessing a disease. Medical imaging data of lungs of a patient is received. The lungs are segmented from the medical imaging data and abnormality regions associated with a disease are segmented from the medical imaging data. An assessment of the disease is determined based on the segmented lungs and the segmented abnormality regions. The disease may be COVID-19 (coronavirus disease 2019) or diseases, such as, e.g., SARS (severe acute respiratory syndrome), MERS (Middle East respiratory syndrome), or other types of viral and non-viral pneumonia.

Description

[0001] Cross References to Related Applications [0002] This application claims the benefit of U.S. Provisional Application No. 63 / 002,457, filed March 31, 2020, the disclosure of which is incorporated herein by reference in its entirety. technical field [0003] The present invention relates generally to the assessment of abnormal regions associated with disease from chest computed tomography images, and in particular to the assessment of abnormal regions associated with COVID-19 (Coronavirus Disease 2019). Background technique [0004] COVID-19 (coronavirus disease 2019) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-Cov2). Common symptoms of COVID-19 include fever, cough and difficulty breathing. In severe cases, COVID-19 can cause pneumonia, severe acute respiratory syndrome and multi-organ failure. In most cases, patients infected with COVID-19 experience mild to moderate symptoms that do not require hospitalization. However...

AI Technical Summary

Problems solved by technology

However, the sensitivity of RT-PCR has been found to be as low as 60% to 70%, potentially leading to false negatives

Additionally, limited availability of RT-PCR test kits leads to undetected spread of COVID-19

Images