Refresher Course: Hybrid, Molecular and Translational Imaging

RC 206 - How AI can help in hybrid imaging

February 26, 10:00 - 11:00 CET

4 min
Chairperson's introduction
12 min
Data acquisition and post-processing: is high-throughput hybrid imaging soon possible?
  1. To learn about different post-processing mechanisms and systematic data acquisition principles.
  2. To appreciate the challenges in acquiring and processing high-quality data.
  3. To understand the opportunity and demand of high-throughput imaging.
12 min
Automatic segmentation in PET imaging: are we there yet?
  1. To learn about the technical basics of image segmentation.
  2. To appreciate the specific challenges of working with hybrid imaging data.
  3. To understand automated PET imaging segmentation's current status and future prospects.
12 min
Integrative analysis of multimodality data
  1. To learn about multimodal data, sources and qualities.
  2. To appreciate the difficulty in integrating data from various sources.
  3. To understand the need for integrative diagnostics
12 min
Let's dive in: case-based use of AI in oncologic hybrid imaging
  1. To learn about currently available AI solutions for oncologic hybrid imaging.
  2. To appreciate how AI-based solutions can aid everyday clinical work with hybrid imaging.
  3. To understand the importance of critical appreciation and reflection on clinical AI applications.
8 min
Panel discussion: Let's be real: what is possible with AI in hybrid imaging today?