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This episode’s guest, Andrew Janowczyk, is a computer scientist who has been active in the field of digital pathology since 2008. Before turning to the field of digital pathology he worked across the globe and across industries.
He was a salmon fisherman in Alaska.
In Austria at the United Nations (UN) International Atomic Energy (IAE) Agency, he significantly contributed to the work that won the UN IAEA a Nobel Peace Prize.
He taught English in China.
He helped build an oil facility in the Nigerian jungle and lived in Nigeria for a while.
Then he lived in Germany…
A close family member diagnosed with cancer made him aware of the field of pathology and he decided to switch gears and put his energy and brainpower into advancing this discipline.
He moved to Mumbai, India to get his Ph.D. and started his digital pathology research. Currently, he is working at the Case Western Reserve University (OH, USA) and Lausanne University (Switzerland).
Fast forward to 2018, after 10 years in the field and after overcoming many challenges, he encountered another one: the suboptimal quality of the whole slides from the TCGA data set ( . To solve this he writes software that excludes all the non-usable regions of the slides and makes it open-source.
Why? Why not commercialize such a useful tool?
Andrew’s answer: “I wanted to release it open source just to fundamentally change the world. I wanted to change the way that we enacted digital pathology as a science, and one of the problems with digital pathology science versus other sciences is that we don’t take measurements. And as soon as we start taking measurements, we have the ability to do better.”
In addition to his main work, Andrew also runs a blog ( with resources for computer scientists working in the field of digital pathology.
Other resources from this episode include:
• Publication: HistoQC: An Open-Source Quality Control Tool for Digital Pathology Slides (
• Publication: Assessment of computerized quantitative quality control tool for kidney whole slide image biopsies (
• HistoQC download page (
• An article on Andrews blog about how to download TCGA digital pathology images (
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