Multiscale subnetwork fusion with adaptive data sampling for brain lesion detection and segmentation

An apparatus comprising:

• means for receiving an input medical image patch depicting one or more lesions;
• means for segmenting the one or more lesions from the input medical image patch using a plurality of machine learning based segmentation networks to respectively generate a plurality of initial segmentation masks, each of the plurality of machine learning based segmentation networks trained to segment lesions from patches with a different field of view size;
• means for generating a final segmentation mask of the one or more lesions based on the plurality of initial segmentation masks;
• and
• means for outputting the final segmentation mask of the one or more lesions.

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 patch depicting one or more lesions;
• segmenting the one or more lesions from the input medical image patch using a plurality of machine learning based segmentation networks to respectively generate a plurality of initial segmentation masks, each of the plurality of machine learning based segmentation networks trained to segment lesions from patches with a different field of view size;
• generating a final segmentation mask of the one or more lesions based on the plurality of initial segmentation masks;
• and
• outputting the final segmentation mask of the one or more lesions.