IKT632 Artificial Intelligence for Medical Image Analysis (Autumn 2026)

Upon completion of the course, students will be able to:

• Identify the basic concepts, terminology, theories, models and methods for medicalimage analysis using artificial intelligence

• Characterize the unique challenges associated with various types of medical imagedata modalities• Describe and implement the commonly used artificial intelligence methods used formedical image analysi

.• Develop and systematically test a number of methods for medical image analysisusing artificial intelligence methods• Choose appropriate evaluation methodologies to evaluate the performance of artificialintelligence methods on biomedical image analysis problems

• Identify limitations of the methods covered in the coursein order to:• Curate medical image data for use in artificial intelligence based methods

• Implement, analyze and evaluate biomedical image analysis systems using artificialintelligence• Use the knowledge acquired in the course read and profit by literature in the area

• Overview of biological and medical imaging modalities and research/clinicalapplications

• Quick introduction to: (a) medical imaging tools (viewers, formats, etc.) and (b)Pytorch/Tensorflow

• Basic Mathematics (Linear Algebra, Probability, and Optimization)

• Challenges in biomedical image data handling and curation• Detection/ Segmentation/ Image classification for biomedical images

• Machine Learning Methods: SVM, PCA, KNN, FCM, etc. applied to medical imageanalysis• Overview of Neural networks and Deep Learning: Principle of learning, CNNs, LossFunctions, etc. for medical image analysis

• Transfer learning, fine tuning, and generalization in medical image analysis

• Evaluation methodology in medical image analysis: metrics, calibration, uncertainty,bias, etc

• Challenges in healthcare Al deployment: reproducibility, interpretability andregulatory

• Unsupervised/self-supervised learning in biomedical image analysis

• Generative models and Inverse problems in medical imaging

To successfully complete the course, students must actively engage in course components,deliver an oral presentation with a Q&A session, and submit a comprehensive mini projectreport.Pass/fail

The course assessment consists of:

• Oral Presentation: Evaluated based on the clarity of communication, understanding oftheoretical concepts, and ability to engage in discussion during the Q&A session.

• Project Report: Assessed for coherence, analytical approach, and relevance,demonstrating the candidate's ability to apply key course concepts.