Multimodal Imaging in AI: A Radiotherapy Point of View

Are you curious about the intersection of medical imaging and artificial intelligence? This interactive workshop is designed for anyone eager to explore AI development using medical imaging techniques like CT, PET, and MRI. Whether you're an AI enthusiast or a budding developer, this session will equip you with the knowledge and skills to tackle real-world healthcare challenges.

About the speaker

Luis de la O Arevalo is a Junior Academic Teacher and PhD candidate in Deep Learning at the Department of Radiotherapy, UMCG. He specializes in developing segmentation and prediction models for radiotherapy applications, with experience in CT, PET, and other modalities of medical imaging. Passionate about bridging the gap between AI and clinical practice, Luis combines his research expertise with a love for teaching to inspire and equip others in the field.

Why Attend?

• Gain insights into the clinical applications and usability of imaging modalities.
• Learn how to preprocess, normalize, and label medical images effectively.
• Discover how to design AI models tailored to specific clinical needs.
• Bridge the gap between engineering and clinical expectations for AI development.

Who Should Attend?

No medical background is required—this workshop is for anyone with:

• Basic knowledge/familiarity with image processing and AI concepts, such as:
  - Image Processing: Contrast, Histogram, Matrices, Pixel.
  - AI:  Labels, Inputs, Outputs, Network, Training, Testing, Dataset
• Familiarity with basic Python programming (using Jupyter notebooks).
• An interest in applying AI to healthcare challenges.

What to Bring

• A laptop with Wi-Fi access (Eduroam or other) is needed.

• A Google Drive account for using Google Colab.

Workshop Highlights

• Imaging Modalities: Explore the clinical relevance and usability of CT, PET, and MRI imaging, Image Storing, processing and normalisation.
• AI Development: Learn best practices for data preprocessing, labelling, metrics, algorithm selection, and validation.
• Interactive Learning: Hands-on activities and expert guidance,  Engineering vs Clinical Expectations.

Limited to 20 participants!

Register now to secure your spot. Late registrations will be added to a waitlist. Transform multimodal imaging challenges into AI solutions—don’t miss this opportunity!