Bioimage informatics

Bioimage informatics emerges as a growing field on the interface between microscopy, signal processing, and computer science to investigate biological processes. State-of-the-art microscopes produce large volumes of high-resolution multidimensional data (up to 5D). Therefore, powerful and efficient software tools are needed to extract quantitative data from these images automatically.

This course comprehensively overviews recent methods, algorithms, and computer tools used in computational bioimaging and bioimage analysis. It exposes the fundamental concepts and practical computer solutions for extracting quantitative information from multidimensional image data.

Theoretical concepts and practical aspects of the most common image reconstruction and image analysis techniques are introduced. Furthermore, best practices in how to code algorithms and deploy software tools to build automatic analysis workflows (mainly in ImageJ/Fiji) are given. The course content is tailored to the needs of life scientists driven by the need to answer biological questions with the help of image data. Addressed topics include (but are not restricted to) microscopy modalities, digital images, multi-dimensional data manipulation (3D, time, multiple channels), 3D image-processing algorithms, 5D visualisation, reconstruction, deconvolution, denoising, stitching, visual feature detection, model-based and data-driven methods of segmentation, active contours, image analysis workflow, pixel classification, deep learning, and tracking of particles.

The course comprises lectures, workshops with state-of-the-art software packages (napari, ImageJ, Fiji, QuPath), practical hands-on sessions and a mini-project.

A personal laptop is recommended to run (open-source) bioimage software packages. We kindly ask you to download and install Fiji and napari on your computer to guarantee a smooth start to the exercise session. 

Teachers

• Daniel Sage (daniel.sage@epfl.ch)
• Arne Seitz (arne.seitz@epfl.ch)

Teaching Assistants

• Hale-Seda Ivo Radoykova (hale-seda.radoykova@epfl.ch)