Lars Grüter
Lars is currently working as a freelance and core developer for the image processing library scikit-image. With an education in electrical engineering and a focus in health and sensor technologies, he has worked as a research assistant on adaptive ultrasound imaging at the TU Dresden. As a student, he started contributing to the scientific Python ecosystem and discovered his interest for signal processing, Linux, and especially Python’s scientific ecosystem.
Sessions
Between telescopes and satellite cameras and MRI machines and microscopes, scientists are producing more images than they can realistically look at. They need specialized viewers for multi-dimensional images, and automated tools to help process those images into knowledge. In this tutorial, we will cover the fundamentals of algorithmic image analysis, starting with how to think of images as NumPy arrays, moving on to basic image filtering, and finishing with a complete workflow: segmenting a 3D image into regions and making measurements on those regions. At every step, we will visualize and understand our work using matplotlib and napari.