Project description
Advanced tools for the early detection of melanoma
In the fight against cancer, effective screening and early detection are key. Melanoma is one of the most aggressive cancers that can be detected at an early stage. It is responsible for the majority of skin growths. However, current screening methods involve checking each individual pigmented lesion for melanoma signs, which is often inefficient and time-consuming. The EU-funded iToBoS project will develop a groundbreaking AI diagnostic platform to assist in the timely detection of melanoma. The platform will consist of a cutting-edge body scanner and accompanying computer-aided diagnostic tool that will provide accurate, personalised early diagnosis of melanoma, saving lives and healthcare resources worldwide.
Objective
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.
Fields of science
- natural sciencesbiological sciencesgenetics
- medical and health scienceshealth sciencespublic health
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensorsoptical sensors
- medical and health sciencesclinical medicineoncologyskin cancermelanoma
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
Keywords
Programme(s)
Funding Scheme
RIA - Research and Innovation actionCoordinator
17004 Girona
Spain
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Participants (21)
8953 Dietikon
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
49527 Petach Tikva
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28037 Madrid
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Legal entity other than a subcontractor which is affiliated or legally linked to a participant. The entity carries out work under the conditions laid down in the Grant Agreement, supplies goods or provides services for the action, but did not sign the Grant Agreement. A third party abides by the rules applicable to its related participant under the Grant Agreement with regard to eligibility of costs and control of expenditure.
28037 Madrid
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Participation ended
8500 Kortrijk
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157 80 ATHINA
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30167 Hannover
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08036 Barcelona
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Legal entity other than a subcontractor which is affiliated or legally linked to a participant. The entity carries out work under the conditions laid down in the Grant Agreement, supplies goods or provides services for the action, but did not sign the Grant Agreement. A third party abides by the rules applicable to its related participant under the Grant Agreement with regard to eligibility of costs and control of expenditure.
08036 Barcelona
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08173 Sant Cugat Del Valles
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Dundalk Louth
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
34127 Trieste
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17003 Girona
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
31400 Toulouse
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
SW1W 9TR London
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
94160 Saint-Mande
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
4072 Brisbane
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1111 Budapest
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80686 Munchen
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75597 Uppsala
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33604 Bielefeld
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.