Every May 23, society comes together on World Melanoma Day, a date that seeks to raise awareness and promote concrete actions to combat this disease.
The use of 8 dermoscopic modules allowed to explore the scanning of the full-patient body, acquired with the highest resolution requiring a short acquisition time.
iToBoS is presented as a project for the creation of a diagnostic platform to help with the early detection of melanoma.
iToBoS representatives attended the event “Retrieval Augmented Generation (RAG) systems”, organized by Centre of Innovation for Data tech and Artificial Intelligence (CIDAI) online on May 8th, 2024.
Recent 3D registration methods are mostly learning-based that either find correspondences in feature space and match them, or directly estimate the registration transformation from the given point cloud features.
Initially, the system was engineered so that the first step is to map the patient in 3D from a collection of images acquired by the two cameras of the first group (Lucid Helios2+ and Lucid Triton).
The first prototype of iToBoS, conceived at the project’s initial stages was an innovative design that incorporated several arches.
This blog is the next in a series of 5, to discuss the results of the Ethical AI workshop at MPNE Consensus Data 2024.
Artificial intelligence in medical applications is always faced with a series of difficulties. The challenges range from the quality of input data and model performance to ethical problems.
Foundation models have taken the world of AI by storm. These pre-trained powerhouses have revolutionized natural language processing, computer vision, and speech processing, remarkable advancements in various domains.