This is the seventh episode of ACVC Talks on Digital Health series.
Computer vision and deep learning models can be used to perform image analysis tasks such as image classification, object detection, and semantic segmentation. Those tasks are the first blocks to solving real-life problems we come across every day, and are used extensively in medical imaging. Recent algorithm developments accelerate quantitative automated imaging towards the diagnosis of diseases and personalised treatment strategies.
In this video, we extensively review the most famous deep-learning architectures used for image analysis.
The presentation was held by Alessandro Casella, PhD Fellow in Bioengineering, Istituto Italiano di Tecnologia and Politecnico di Milano, Italy.
Our mission: To reduce the burden of cardiovascular disease.