This repository contains a set of Jupyter notebooks that demonstrate various image and metadata workflows by utilising OMERO Plus API.
This notebook demonstrates basic python API calls.
The notebook covers: server connection, image retrieval and query service.
Presented during OMERO Plus for High Content Screening & Analysis: The Gold Standard in Data Management & Integratio webinar.
These notebooks demonstrate how to access the analytical data stored in OMERO using OMERO.tables and file annotations.
The notebooks cover: data retrieval, visualisation, statistical analysis and machine learning.
Preseted during Using PathViewer and Multiplexed Imaging to Advance Cancer Research webinar.
This notebook demonstrates how to read raw image pixels from OMERO Plus, perform image processing using scikit-image and save the analysis results to OMERO Plus. Objects identified by scikit-image algorithms are converted to OMERO region of interests (ROIs) and a set of key - value pairs describing each object.
The notebook covers: raw pixel retrieval, image processing, OMERO ROI creation and saving, OMERO key - value pair creation, saving and linking to ROIs.