The COVID-19 pandemic accelerated the adoption of digital technologies in many areas of medicine.

In this blog we present more details about the iToBoS dataset: skin region images extracted from 3D total body photographs for lesion detection.

iToBoS research partners from The University of Queensland have recently published an invited article with the Italian Journal of Dermatology and Venereology, titled ‘Genetic testing for familial melanoma’. 

The Hospital Operator Interface, or HMI, plays a crucial role in the operation of the scanner.

An AI cognitive assistant is developed that will fuse information from multiple data sources, providing melanoma risk estimation both on the patient level as well as per-lesion.

The initial and crucial step in total body imaging involves the optical imaging unit. Illumination is provided by 10 high-brightness LEDs, delivering over 150,000 lumens for uniformly distributed lighting.

In developing the "Arch" prototype of the scanner, patient safety was paramount.

To date, majority of AI tools for skin cancer monitoring only assess single lesion images, in isolation of any patient clinical background.  

3D cameras gather detailed information about the three-dimensional shape of the patient being scanned.

Quantitative risk estimation based on clinical data, typically collected through patient questionnaires, is based on linear regression models that are readily interpretable by clinicians.