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title: Introductory image processing on biological images using python.
URL: https://github.com/dwaithe/model-training/
Short description: A jupyter notebook python practical designed to give students a introduction to opening and processing image files derived from biological samples.
Long description: This is an image processing practical for students with an interest in analysing biologically derived images. It is written in the language python and utilises jupyter notebook for annotation and visualisation of the code. The practical is beginner level, although some knowledge of python is recommended. In this practical students will learn to open single images as well as multi-page tiff files. Users will then learn to apply simple thresholding to an image and image-stacks and will learn to apply a variety of image filters to process the data. The practical is accompanied by lecture slides which give an introduction to image processing.
This training material was developed as model user case for the GBI/ELIXIR/EuBI/NEUBIAS hackathon 2018 hosted at Cambridge University.
Nodes: United Kingdom
Target Audience:
- Bioimage analysts
- Image analysts
- Computer vision scientists
- Bioinformaticians
- Computer Scientists
- Biophysicists
- Biologists
- Microscopists
- PhD students
- DPhil students
Resource Type:
- jupyter notebooks
- pdf slides
Licence: MIT
Authors:
- Dominic Waithe
Contributers:
- Anatole Chessel
- Volker Baecker
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