Systems, methods, and devices for diagnostics based on live un-scattering computational imaging

A system for identifying micron-scale features below a surface of a live human tissue, the system comprising:

• one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for:
• emitting from one or more emitters at the surface of the live human tissue electromagnetic signals capable of penetrating human tissue of different densities;
• obtaining from a sensor positioned at the surface of the live human tissue electromagnetic signals reflected from or transmitted through live human tissues of different densities as one or more obtained images;
• inputting the one or more obtained images into a machine learning model, wherein the machine learning model is trained to:
• identify scattering of certain electromagnetic signals comprising each of the one or more obtained images;
• correct for the scattering to create one or more images of live human tissues at one or more subsurface tissue depths;
• and
• identify micron-scale features of interest within the one or more images of live human tissues at the one or more subsurface tissue depths.

A non-transitory computer-readable storage medium storing one or more programs for identifying micron-scale features below a surface of a live human tissue, the one or more programs comprising instructions, which when executed by one or more processors of an electronic device, cause the electronic device to:

• emit from one or more emitters at the surface of the live human tissue electromagnetic signals capable of penetrating human tissue of different densities;
• obtain from a sensor positioned at the surface of the live human tissue electromagnetic signals reflected from or transmitted through live human tissues of different densities as one or more obtained images;
• input the one or more obtained images into a machine learning model, wherein the machine learning model is trained to:
• identify scattering of certain electromagnetic signals comprising each of the one or more obtained images;
• correct for the scattering to create one or more images of live human tissues at one or more subsurface tissue depths;
• and
• identify micron-scale features of interest within the one or more images of live human tissues at the one or more subsurface tissue depths.

A device for identifying micron-scale features below a surface of a live human tissue, the device comprising:

• one or more emitters at the surface of the live human tissue configured to emit electromagnetic signals capable of penetrating human tissue of different densities;
• at least one sensor positioned at the surface of the live human tissue configured to detect electromagnetic signals reflected from or transmitted through live human tissues of different densities as one or more obtained images;
• one or more processors;
• and
• a memory storing computer instructions that when executed by the one or more processors, cause the device to:
• input the one or more obtained images into a machine learning model, wherein the machine learning model is trained to:
• identify scattering of certain electromagnetic signals comprising each of the one or more obtained images;
• correct for such scattering to create one or more images of live human tissues at one or more subsurface tissue depths;
• and
• identify micron-scale features of interest within the one or more images of live human tissues at the one or more subsurface tissue depths.