Genetic Testing for Familial Melanoma

24/12/2024.

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 of the first scanner prototype

19/12/2024.

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

Development of a cloud-based AI cognitive assistant for holistic melanoma risk estimation

13/12/2024.

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.

High-Resolution Imaging Module for precise skin condition monitoring

9/12/2024.

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.

Patient protection in the first scanner prototype

2/12/2024.

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

iToBoS presented in the first ever HUN-REN Cloud Meetup

28/11/2024.

The first national HUN-REN Cloud Meeting took place in November 28th, hosted at the HUN-REN Wigner Research Center for Physics in Csillebérc.

Development and publication of the clinical study protocol for transparency and reproducibility

26/11/2024.

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

iToBoS presented in CILAD 2024

23/11/2024.

Dr. J. Malvehy was a speaker at the XXIV Ibero-Latin American Dermatology Congress (CILAD), held in Cartagena de Indias, Colombia, from November 19 to 23, 2024.

Why is important the use of 3D cameras?

22/11/2024.

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

Development of novel algorithms for quantitative risk assessment based on clinical and imaging phenotyping data

18/11/2024.

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