Advanced masking technologies in the iToBoS project

Data masking is the process by which sensitive data is replaced, with data that is unintelligible to the receiver, addressing data security and privacy requirements and regulations.

Medical Informatics Europe Conference

I recently took part in MIE conference in Nice, France. This year the conference focus was on “challenges of trustable AI and added value on Health”.

Dermatology on the beach in Grado (Italy)

The team of the Dermatological Unit of the University of Trieste, leaded by Professor Iris Zalaudek, offered three days (15-17 June 2022) of skin screening directly on the beach of Grado (Italy).

Building of the iToBoS Cloud: Background

The success of new scientific research, such as the novel holistic approach for melanoma detection in iToBoS, is increasingly dependent on the efficient storage and processing of copious amounts of data originating from research. Moreover, the scientists often require complex, large-scale platforms based on the coordinated operation of multiple components.

Relevance-based Neural Freezing against Catastrophic Forgetting in Neural Network Training

The ability to continuously process and retain new information like we do naturally as humans is a feat that is highly sought after when training neural networks.

Liquid lenses for fast focusing in machine vision. Technical bases

Tunable lenses are conceptionally like a human eye. An elastic polymer membrane covers a reservoir containing an optical liquid.

Liquid lenses for fast focusing in machine vision

The iToBoS project is usually categorized within the field of medical imaging. However, all the technical solutions used or to be developed in the project, from the optics to the artificial intelligence algorithms, are part of the wider field of machine vision.

Invertible Denoising Network: A Light Solution for Real Noise Removal

The task of real-world noise removal is challenging, as the noise model is highly complex. CNNs have lately achieved state-of-the-art denoising performance, but the networks are extremely large and complicated for a better accuracy.

Diffusion Models

Diffusion Models are a type of likelihood-based models that have recently generated synthetic images of excellent quality.

New scenarios of the teledermatology

In this article we analyze new scenarios and business cases of teledermatology.