2025-04-25 –, Europium2
While trees and human brains don't share that many properties regarding their domain, the analysis of the height of a tree and cancer in human brains does.
This talk provides a not-so-serious introduction to the domain of computer vision for pathological use cases.
Besides a general introduction to (digital) pathology and the technical similarities between satellite images (GeoTIFs) and pathological images (Whole-Slide Images), we will take a look at computer vision (both ML-based and conventional) on Python.
Whether you have never done image processing in Python, are an expert (ready to share some tricks with me), or are just curious to see pictures of a human brain, this talk is for you.
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".
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.
The main content is:
- a short introduction to digital pathology (know your domain)
- the similarities between a tree and your brain (technically speaking, there are a lot)
- 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
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".
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Expected audience expertise: Python:Intermediate
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.