PHYS-647 / 2 credits

Teacher: Invited lecturers (see below)

Language: English


Frequency

Only this year

Summary

This course introduces students to the basics of image data science using Napari and Python. Students will learn image filtering, segmentation and feature extraction. Other topics include supervised and unsupervised machine learning techniques for object classification and clustering.

Content

Note

Lecturers: Robert Haase and Till Korten (Technische Universität Dresden)

Host: S. Manley

Keywords

Python, Napari, bio-image analysis

Learning Prerequisites

Required courses

Minimal python skills

Learning Outcomes

By the end of the course, the student must be able to:

  • to analyze microscopy images, e.g. segmenting nuclei in one image channel and measuring intensity in another channel
  • Apply this to a folder of images
  • Do basic statistics, compare conditions

In the programs

  • Number of places: 30
  • Exam form: Oral presentation (session free)
  • Subject examined: Image data science with Python and Napari
  • Lecture: 16 Hour(s)
  • Exercises: 16 Hour(s)

Reference week