Have a quick look at the iToBoS scanner prototype at the Bosch Manufacturing Solutions facilities.

The demand for mobile and multitask devices has shifted the focus of research towards embedded systems and microcomputers.

Understanding the geometry of an existing scene and being able to use this knowledge to produce (and refine) data, is an important task in any research field, particularly in the medical domain where the study and understanding of 3D structures of interest play a crucial role in abnormality detection.

The iToBoS project is a demonstration of collaborative efforts, where multiple partners combine their specialized knowledge towards a common objective.

Precision and diversity are crucial in melanoma research, and isahit's approach to data annotation reflects this necessity.

The need to analyze personal data to drive business, alongside the requirement to preserve the privacy of data subjects, creates a known tension.

An important challenge for applying machine and deep learning methods in applications where data collection is difficult, or costly is the reduced amount of annotated data.

Precision and expertise are necessary to reach 100% quality in data annotation. The process of selecting image annotators, called HITers at isahit, for projects like iToBoS involves rigorous criteria to ensure the highest quality in final annotations.

Self-attention is the core mechanism behind Transformer models, which have provided state-of-the-art results in various scientific fields (i.e. Natural Language Processing).

What benefits does AI offer digital pathologists? How can it revolutionize the field and what are its biggest challenges?