iToBos

iToBoS – Intelligent Total Body Scanner for Early Detection of Melanoma

Project reference: EIN2020-112457
Coordinators: UNIVERSITAT DE GIRONA
EU Budget: 11 039 139,25 €
Duration: 01/04/2021 – 31/03/25
UdG Project Coordinator: Dr Rafa Garcia

Summary

Melanoma is one of the most aggressive cancers that can be discovered at an early stage, and it is responsible for 60% of lethal skin neoplasia. Its incidence has been increasing in white population and could become a public health challenge because of an increase in life expectancy of the elderly population. Total body skin examination, the primary screening mechanism for melanoma, checks each pigmented skin lesion individually in search of typical melanoma signs. This can be a very time consuming technique for patients with atypical mole syndrome or a large number of naevi.

 

iToBoS aims at developing an AI diagnostic platform for early detection of melanoma. The platform includes a novel total body scanner and a Computer Aided Diagnostics (CAD) tool to integrate various data sources such as medical records, genomics data and in vivo imaging. This approach will lead to a highly patient-tailored, early diagnosis of melanoma. The project will develop and validate an AI cognitive assistant tool to empower healthcare practitioners, offering a risk assessment for every mole. Beyond integrating all available information about the patient to personalise the diagnostic, it will provide methods for visualising, explaining and interpreting AI models, thus overcoming the “black box” nature of current AI-enabled CAD systems, and providing dermatologists with valuable information for their clinical practice.

 

The new total body scanner will be based on an existing prototype developed by 3 of the project partners, but powered with high-resolution cameras equipped with liquid lenses. These novel lenses, based on two immiscible fluids of different refractive index, will allow achieving unprecedented image quality of the whole body. The integration of such images with all available patient data using machine learning will lead to a new dermoscopic diagnostic tool providing prompt, reliable and highly personalised diagnostics for optimal judgement in clinical practice.

PARTNERS

 

Coordinator: UNIVERSITAT DE GIRONA
OPTOTUNE SWITZERLAND AG
IBM ISRAEL – SCIENCE AND TECHNOLOGY LTD
ROBERT BOSCH ESPANA FABRICA MADRID SA
BARCO NV
NATIONAL TECHNICAL UNIVERSITY OF ATHENS – NTUA
GOTTFRIED WILHELM LEIBNIZ UNIVERSITAET HANNOVER
FUNDACIO CLINIC PER A LA RECERCA BIOMEDICA
RICOH SPAIN IT SERVICES SLU
TRILATERAL RESEARCH LIMITED
UNIVERSITA DEGLI STUDI DI TRIESTE
CORONIS COMPUTING SL
TORUS ACTIONS
V7 LTD
ISAHIT
THE UNIVERSITY OF QUEENSLAND
SZAMITASTECHNIKAI ES AUTOMATIZALASI KUTATOINTEZET
FRAUNHOFER GESELLSCHAFT ZUR FOERDERUNG DER ANGEWANDTEN FORSCHUNG E.V.
MELANOMA PATIENT NETWORK EUROPE

CATEGORY IMAGE ANALYSIS