Method to detect white blood cells and/or white blood cell subtypes from non-invasive capillary videos

A method to detect white blood cells and/or white blood cell subtypes from non-invasive capillary videos, the method comprising:

• acquiring a first plurality of images of a region of interest including one or more capillaries of a predetermined area of a human subject from non-invasive capillary videos captured with an optical process;
• processing the first plurality of images to determine one or more optical absorption gaps located in said capillary;
• annotating the first plurality of images with an indication of any optical absorption gap detected in the first plurality of images;
• and
• determining a presence of white blood cells and/or the subtype of any white blood cells present in the one or more optical absorption gaps using the first plurality of images and annotated information from the first plurality of images and information from a machine learning subsystem which has learned and determined the presence of white blood cells and/or the subtype of white blood cells present in one or more optical absorption gaps using annotated information from a second plurality of images acquired with an advanced optical process.

A method to determine a density of red blood cells from non-invasive capillary videos, the method comprising:

• acquiring a first plurality of images of a region of interest including one or more capillaries of a predetermined area of a human subject from non-invasive capillary videos captured with an optical process;
• processing the first plurality of images to determine one or more areas of hemoglobin optical absorption gaps located in said capillary;
• annotating the first plurality of images with an indication of any areas of hemoglobin optical absorption gaps detected in the first plurality of images;
• acquiring a second plurality of images of the same region of interest of the same capillary with an advanced optical process capable of resolving cellular structure of red blood cells;
• spatiotemporally annotating the second plurality of images with an indication of a density of any red blood cells detected in the second plurality of images;
• and
• determining the density of any red blood cells present in the one or more optical absorption gaps using a machine learning subsystem.