Assessment of abnormality patterns associated with covid-19 from x-ray images

An apparatus comprising:

• means for receiving an input medical image in a first modality;
• means for segmenting lungs from the input medical image using a trained lung segmentation network;
• means for segmenting abnormality patterns associated with a disease from the input medical image using a trained abnormality pattern segmentation network;
• and
• means for determining an assessment of the disease based on the segmented lungs and the segmented abnormality patterns,
• wherein the trained lung segmentation network and the trained abnormality pattern segmentation network are trained based on 1) synthesized images in the first modality generated from training images in a second modality and 2) target segmentation masks for the synthesized images generated from training segmentation masks for the training images.

A non-transitory computer readable medium storing computer program instructions, the computer program instructions when executed by a processor cause the processor to perform operations comprising:

• receiving an input medical image in a first modality;
• segmenting lungs from the input medical image using a trained lung segmentation network;
• segmenting abnormality patterns associated with a disease from the input medical image using a trained abnormality pattern segmentation network;
• and
• determining an assessment of the disease based on the segmented lungs and the segmented abnormality patterns,
• wherein the trained lung segmentation network and the trained abnormality pattern segmentation network are trained based on 1) synthesized images in the first modality generated from training images in a second modality and 2) target segmentation masks for the synthesized images generated from training segmentation masks for the training images.