Introduction to Digital Pathology using QuPath

This course is an introduction to Image Processing and Analysis using QuPath, an open source software dedicated to processing histopathological datasets. The course will be lectured by Pete Bankhead, a lead developer of QuPath, and an author of an excellent ImageJ book, supported by ScopeM IDA: Szymon Stoma and Simon F. Nørrelykke. Pete recently left Queen's University Belfast to join Philips Digital Pathology Solutions in Belfast. The attendees will learn the fundamentals of image analysis including how to do basic Macro programming in QuPath for automated batch analysis of images, and will be introduced to visualisation and explorative data analysis after extraction of numerical data from images.

Time:
21st - 23th November 2017

Place:
ETH Campus Hoenggerberg

Zurich, Switzerland

Tue. 11:00 - 18:00*, HPI F16

Wed. 9:00 - 18:00*, HPZ E35

Thu. 9:00 - 18:00*, HPZ E35

* last +-2hrs are individual project work

Deadline for application:
12-noon, October 6th, 2017 (changed from 12-noon on September 30th, 2017)

Cost:
100 CHF academia / 400 CHF industry

Applying:

Using a linked form 

Day 1

- QuPath background

- Viewing & annotating images

- Three ways to count cells

- Introduction to classifiers

- QuPath & ImageJ

- Discussion & projects

Day 2

- Superpixels & tile classification

- Concepts: objects, hierarchies & classifications

- Introduction to Groovy

- Automating analysis with Groovy

- Discussion & projects

Day 3

- More sophisticated scripting

- Anything else that could not be fitted in earlier...

- Discussion & projects

QuPath aims to help improve the speed, objectivity and reproducibility of digital pathology analysis and biomarker interpretation by offering an open, powerful, flexible, extensible software platform for whole slide image analysis.

QuPath has been developed for research applications at the Centre for Cancer Research & Cell Biology at Queen's University Belfast, as part of research projects funded by Invest Northern Ireland and Cancer Research UK.

A preprint describing QuPath is now available at
http://biorxiv.org/content/early/2017/01/12/099796

Screenshots

[1] QuPath: https://qupath.github.io/

[2] QuPath pub: http://biorxiv.org/content/early/2017/01/12/099796

[3] Workshop poster: https://polybox.ethz.ch/index.php/s/FHQaseMKNvXwP02