"Meet iToBoS" worksop series: Ethical AI in iToBoS

31/05/2024.

On Friday 31st of May 2024, the MPNE hosted the latest instalment of the “Meet iToBoS” online workshop series.

Data acquisition and transmission to the main computer in the first scanner prototype

27/05/2024.

The process of data acquisition involves capturing dermoscopic images using the High-definition Imaging Module (HDIM).

iToBoS at AEDV'24: "Artificial intelligence: Innovations with impact on daily life in Dermatology"

24/05/2024.

On May 24, 2024, at the AEDV Congress in Madrid, Spain, Dr. J. Malvehy gave the presentation titled "Artificial intelligence: Innovations with impact on daily life in Dermatology. Cancer and ChatGPT".

iToBoS at AEDV'24: "Update on melanoma: Present and future"

23/05/2024.

On May 23, 2024, at the AEDV Congress in Madrid, Spain, Dr. J. Malvehy, presented a conference titled "Update on melanoma: Present and future."

World Melanoma Day: A call for skin cancer awareness and prevention

23/05/2024.

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.

Final prototype: the vision system

21/05/2024.

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 at 16th Optatec in Frankfurt

16/05/2024.

The iToBoS project was presented at the 16th Optatec from 14 - 16 of May 2024 in Frankfurt, Germany.

iToBoS presented in the Scientific Cultural Calendar of the Spanish embassy in Switzerland and Liechtenstein

15/05/2024.

iToBoS is presented as a project for the creation of a diagnostic platform to help with the early detection of melanoma.

Retrieval Augmented Generation (RAG) systems

9/05/2024.

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.

3D registration methods with a featureless baseline and an unbiased benchmark

6/05/2024.

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.