A patient will enter a room and the scanner will move to acquire images of their body surface, and that’s it! The scanner will look like a series of cameras in an arch that moves.
The iToBoS plans to run its first trials with half the participants being at high risk for melanoma and half at low risk, in order to collect data on a balanced set of healthy and at-risk patients. The patient’s personally identifiable features are excluded from the photography, and a mole-map of the patient is generated with the help of a sole technician.
Whilst there have been previous technologies to fully map the surface of a human’s skin for mole classification, iToBoS will capture a higher resolution of each mole, and combine additional sources of information to determine the level of risk of melanoma for each lesion.
The goal is to build a machine that captures the same image resolution of a dermoscope, a handheld device that dermatologists are used to analyzing, but doing so automatically through the robotic movement of cameras, and utilizing AI to identify and crop each lesion across the body whilst anonymizing personally identifiable features.