Mit (18)#
BioEngine Documentation#
[‘Wei Ouyang’, ‘Nanguage’, ‘Jeremy Metz’, ‘Craig Russell’]
Licensed MIT
BioEngine, a Python package designed for flexible deployment and execution of bioimage analysis models and workflows using AI, accessible via HTTP API and RPC.
Tags: Workflow Engine, Deep Learning, Python
Content type: Documentation
CellTrackColab#
[‘Guillaume Jacquemet’]
Licensed MIT
Content type: Notebook, Collection
Collection of teaching material for deep learning for (biomedical) image analysis#
[‘Constantin Pape’]
Licensed MIT
Tags: Artificial Intelligence, Bioimage Analysis
Data Carpentry for Biologists#
Licensed [‘CC-BY-4.0’, ‘MIT’]
Content type: Tutorial, Code
Deep Vision and Graphics#
[‘Victor Yurchenko’, ‘Fedor Ratnikov’, ‘Viktoriia Checkalina’]
Licensed MIT
Tags: Python, Artificial Intelligence
Content type: Notebook
Galaxy Training Material#
Licensed MIT
Content type: Slides, Tutorial
Image analysis course material#
[‘Christian Tischer’]
Licensed MIT
Training materials about image registration, big warp and elastix
Image processing with Python#
[‘Guillaume Witz’]
Licensed MIT
Series of Notebooks exposing how to do mostly basic and some advanced image processing using Python. It uses standard packages (Numpy, Maplotlib) and for the image processing parts is heavily based on the scikit-image package.
Tags: Python
Content type: Notebook
Intro napari slides#
[‘Peter Sobolewski’]
Licensed MIT
Introduction to napari workshop run at JAX (Spring 2024).
Tags: Napari
Content type: Slides
https://thejacksonlaboratory.github.io/intro-napari-slides/#/section
Introduction to Deep Learning for Microscopy#
[‘Costantin Pape’]
Licensed MIT
This course consists of lectures and exercises that teach the background of deep learning for image analysis and show applications to classification and segmentation analysis problems.
Tags: Deep Learning, Pytorch, Segmentation, Python
Content type: Notebook
OMERO - HCS analysis pipeline using Jupyter Notebooks#
[‘Riccardo Massei’]
Licensed MIT
Material and solutions for the course ‘Bioimage data management and analysis with OMERO’ held in Heidelberg (13th May 2024) - Module 3 (1.45 pm - 3.45 pm): OMERO and Jupyter Notebooks. Main goal of the workflow is to show the potential of JN to perform reproducible image analysis in connection with an OMERO instance. In this specific example, we are performing a simple nuclei segmentation from raw images uploaded in OMERO.
Tags: Teaching, Bioimage Analysis, Notebooks, Python, Omero
Content type: Github Repository
Python BioImage Analysis Tutorial#
[‘Jonas Hartmann’]
Licensed MIT
Tags: Python, Bioimage Analysis
Python for Microscopists#
[‘Sreenivas Bhattiprolu’]
Licensed MIT
Tags: Python, Bioimage Analysis
Content type: Notebook, Collection
Teaching Bioimage Analysis with Python#
[‘Rafael Camacho’]
Licensed MIT
Tags: Python, Bioimage Analysis
Content type: Tutorial
Teaching ImageJ FIJI#
[‘Rafael Camacho’]
Licensed MIT
Tags: Fiji, Bioimage Analysis
Content type: Tutorial
The Turing Way: Guide for reproducible research#
Licensed [‘CC-BY-4.0’, ‘MIT’]
A guide which covers topics related to skills, tools and best practices for research reproducibility.
Content type: Book
https://the-turing-way.netlify.app/reproducible-research/reproducible-research
Workshop-June2024-Madrid#
Licensed MIT
Tags: Bioimage Analysis
Content type: Workshop, Collection
ZeroCostDL4Mic: exploiting Google Colab to develop a free and open-source toolbox for Deep-Learning in microscopy#
[‘Lucas von Chamier’, ‘Romain F. Laine’, ‘Johanna Jukkala’, ‘Christoph Spahn’, ‘Daniel Krentzel’, ‘Elias Nehme’, ‘Martina Lerche’, ‘Sara Hernández-pérez’, ‘Pieta Mattila’, ‘Eleni Karinou’, ‘Séamus Holden’, ‘Ahmet Can Solak’, ‘Alexander Krull’, ‘Tim-Oliver Buchholz’, ‘Martin L Jones’, ‘Loic Alain Royer’, ‘Christophe Leterrier’, ‘Yoav Shechtman’, ‘Florian Jug’, ‘Mike Heilemann’, ‘Guillaume Jacquemet’, ‘Ricardo Henriques’]
Licensed MIT
Content type: Notebook, Collection
https://www.nature.com/articles/s41467-021-22518-0
https://doi.org/10.1038/s41467-021-22518-0