Carrara F., Ciampi L., Di Benedetto M., Falchi F., Gennaro C., Amato G.
AI for Healthcare Computer vision Deep Learning Medical image analysis
The application of Artificial Intelligence technologies in healthcare can enhance and optimize medical diagnosis, treatment, and patient care. Medical imaging, which involves Computer Vision to interpret and understand visual data, is one area of healthcare that shows great promise for AI, and it can lead to faster and more accurate diagnoses, such as detecting early signs of cancer or identifying abnormalities in the brain. This short paper provides an introduction to some of the activities of the Artificial Intelligence for Media and Humanities Laboratory of the ISTI-CNR that integrate AI and medical image analysis in healthcare. Specifically, the paper presents approaches that utilize 3D medical images to detect the behavior-variant of frontotemporal dementia, a neurodegenerative syndrome that can be diagnosed by analyzing brain scans. Furthermore, it illustrates some Deep Learning-based techniques for localizing and counting biological structures in microscopy images, such as cells and perineuronal nets. Lastly, the paper presents a practical and cost-effective AI-based tool for multi-species pupillometry (mice and humans), which has been validated in various scenarios.
Source: Ital-IA 2023, pp. 128–133, Pisa, Italy, 29-31/05/2023
@inproceedings{oai:it.cnr:prodotti:488199, title = {AIMH Lab 2022 activities for Healthcare}, author = {Carrara F. and Ciampi L. and Di Benedetto M. and Falchi F. and Gennaro C. and Amato G.}, booktitle = {Ital-IA 2023, pp. 128–133, Pisa, Italy, 29-31/05/2023}, year = {2023} }