Body imaging and diagnostic system

A method of detecting skin conditions, the method comprising the steps of

• capturing a first image scan,
• identifying areas of interest of the first image scan using a trained custom image segmentation model, wherein the trained custom image segmentation model is trained using a first plurality of image scans,
• classifying each of the areas of interest to correspond to skin conditions, wherein the skin conditions include at least one of eczema, hives, contact dermatitis, autoimmune skin conditions, bacterial infections, viral infections, fungal infections, burns, scars, grafts, childhood skin conditions, skin cancers, and psychosomatic skin disorders, routing each of the areas of interest to at least one trained specialist model, the trained specialist model corresponding to one or more of the skin conditions, wherein the at least one trained specialist model is a deep neural network trained using a second plurality of image scans,
• classifying the areas of interest using the at least one trained specialist model,
• extracting a deep feature layer of the at least one trained specialist model for each of the areas of interest,
• calculating a skin condition metric for each of the areas of interest using the deep feature layer, the skin condition metric corresponding to a standardized scoring system for evaluating at least one of the skin conditions,
• displaying the skin condition metric associated with each of the areas of interest in accordance with the first image scan,
• displaying ranked areas of interest identified in the first image scan ranked in accordance with the classifications.

A skin condition detection system comprising

• an imaging device configured to capture a first image scan of a first user,
• a plurality of datasets that include a plurality of image scans of multiple users,
• a database configured to store the first image scan and the plurality of image scans,
• a trained image segmentation model, wherein the trained image segmentation model is trained using the plurality of image scans stored on the database, and is configured to identify areas of interest corresponding to classifications of skin conditions and to output segmented image data for each of the areas of interest,
• at least one trained specialist model configured to receive the segmented image data and to classify the segmented image data for each of the areas of interest for at least one of the skin conditions, and
• a display configured to display a skin condition metric based on a standardized scoring system for evaluating at least one of the skin conditions for each of the areas of interest, and ranked areas of interest identified in the first image scan ranked in accordance with the classified segmented image data.