Today, we spoke to Karen Gorp, one of our colleagues from Melanoma Patients Australia about why she thinks Early Detection is important for Melanoma patients and her hopes for iToBoS!

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.

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”.

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).

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.

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.

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

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.

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