DD2361/FDD3020 HT26 Advanced Topics in Deep Learning in Biomedical Image Analysis

Welcome! In this course you will develop the conceptual and practical skills needed to build and evaluate AI-based solutions for clinical and biological image data. We will work across the biomedical image-analysis pipeline, including data curation, segmentation, classification and generative modelling.

Overview. Start with Course Information for the learning activities, prerequisites and course organization. Lecture notes, practice quizzes and Colab exercises are organized into Modules. This is a flipped classroom: you read the lecture notes and complete practice quizzes before class. Exercises are available one week in advance and are demonstrated in person during class. The midterm and final quiz are in person and proctored, but will be done on Canvas. Zoom link for TA help sessions and make-up exams: zoom link.

Questions. Follow the Communications Policy. Check the FAQ, then ask in General Discussion. For personal matters, contact Gisele Miranda (gmirand@kth.se), Kevin Smith (ksmith@kth.se) or Emir Konuk (ekonuk@kth.se).

Schedule. The course summary below lists dated course events and assignments. Our eight in-person sessions are at SciLifeLab, Tomtebodavägen 23, Solna (on the 7th floor of the Gamma building).