3/01/2025.

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

30/12/2024.

The goal of this competition is to develop state-of-the-art machine learning techniques for detecting multiple skin lesions in clinical images.

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’. 

19/12/2024.

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

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.

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.

2/12/2024.

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

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.

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.  

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.