Training image curation via hidden feature concatenation

A computer-implemented method, comprising:

• accessing, by a device operatively coupled to a processor, a plurality of medical images and a suite of first deep learning neural networks, wherein the suite of first deep learning neural networks are pre-trained to perform respective inferencing tasks for inputted images depicting respective anatomies or generated by respective imaging modalities;
• curating, by the device, the plurality of medical images in preparation for training of a second deep learning neural network, based on generating for each of the plurality of medical images a respective concatenated embedding that is composed of hidden feature maps extracted from the suite of first deep learning neural networks;
• and
• training, by the device and after such curation, the second deep learning neural network on at least some of the plurality of medical images.

A computer program product for facilitating training image curation via hidden feature concatenation, the computer program product comprising a non-transitory computer-readable memory having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to:

• access a plurality of medical images and a suite of first deep learning neural networks, wherein the suite of first deep learning neural networks are pre-trained to perform respective inferencing tasks for inputted images depicting respective anatomies or generated by respective imaging modalities;
• curate the plurality of medical images in preparation for training of a second deep learning neural network, based on generating for each of the plurality of medical images a respective concatenated embedding that is composed of hidden feature maps extracted from the suite of first deep learning neural networks;
• and
• train, after such curation, the second deep learning neural network on at least some of the plurality of medical images.