What do a tree and the human brain have in common-a not so serious introduction to digital pathology

Friday 14:40 in Europium2

Inspired by last year's talk about the height of a tree [🌳 The taller the tree, the harder the fall. Determining tree height from space using Deep Learning and very high resolution satellite imagery 🛰️] and the strong similarities between optical high resolution satellite images and pathological images, this talk will give a not-so-serious introduction to a quite serious topic: Python for digital pathology. The main content is:

"Cancer detection"
An introduction to (digital) pathology (know your domain)
The similarities between a tree and your brain (technically speaking, there are a lot)
A shallow view of ML-based and conventional computer vision in Python with some practical use cases
Why we can steal (nearly) everything from radiology and get away with it
What potential pitfalls could be
How you can start doing medical computer vision on your own

Warning: this talk contains quite abstract pink-ish pictures of human tissue (and trees^^). If you are unsure this is something you are comfortable with (have a friend), do a quick search for "HE-stained whole-slide image".

Daniel Hieber

Hi, I'm Daniel, a PhD student in digital neuropathology at Julius-Maximilians-University Würzburg and a research associate at the University Hospital Augsburg as well as Neu-Ulm University of Applied Sciences. My work focuses on applying computer vision techniques to automate analysis processes in the pathological departments and provide physicians with the tools to conduct machine learning on their own.