Conexiant
Login
  • The Analytical Scientist
  • The Cannabis Scientist
  • The Medicine Maker
  • The Ophthalmologist
  • The Pathologist
  • The Traditional Scientist
The Pathologist
  • Explore Pathology

    Explore

    • Latest
    • Insights
    • Case Studies
    • Opinion & Personal Narratives
    • Research & Innovations
    • Product Profiles

    Featured Topics

    • Molecular Pathology
    • Infectious Disease
    • Digital Pathology

    Issues

    • Latest Issue
    • Archive
  • Subspecialties
    • Oncology
    • Histology
    • Cytology
    • Hematology
    • Endocrinology
    • Neurology
    • Microbiology & Immunology
    • Forensics
    • Pathologists' Assistants
  • Training & Education

    Career Development

    • Professional Development
    • Career Pathways
    • Workforce Trends

    Educational Resources

    • Guidelines & Recommendations
    • App Notes

    Events

    • Webinars
    • Live Events
  • Events
    • Live Events
    • Webinars
  • Profiles & Community

    People & Profiles

    • Power List
    • Voices in the Community
    • Authors & Contributors
  • Multimedia
    • Video
    • Podcasts
    • Pathology Captures
Subscribe
Subscribe

False

The Pathologist / Issues / 2023 / Jul / Speaking the Same Language
Digital and computational pathology Profession Digital Pathology

Speaking the Same Language

Consistent communication is key to bridge the knowledge gap between computer scientists, and pathologists

By Aleksandra Zuraw 07/06/2023 4 min read

Share

Negative stereotypes about pathologists have long plagued the field. The average person may imagine a pathologist as someone who spends most of their time practicing medicine, alone, in front of a microscope – someone who only communicates through report writing, who chose this specialty because they don't want the challenges that come with treating patients. Now, imagine another stereotypical professional – an introvert sat at their computer, writing code to analyze images. The professional is very good at what they do, but chooses not to be bothered by other people. A computer scientist. 

Computational pathology is a new medical discipline that combines pathology with computer science, and more precisely, computer vision. In the classical workflow, pathology images come from glass slides that are viewed through the eyepiece of a microscope. Now, in the form of whole slide images, they can be viewed on the computer screen – but more importantly, they can be analyzed with computer algorithms!

There is an opportunity to automate repetitive tasks such as cell counting, and even unlock molecular properties of analyzed tissue without the need to perform expensive tests. To maximize this potential, we need one thing: a close collaboration between pathologists and computer scientists. The pathologist needs to learn about image analysis tools and the scoring systems. The computer scientist needs to understand the pathology workflow, terminology, and have a basic understanding of different tissue components.

When collaborating on a computational pathology project, both the pathologist and the computer scientist take out their respective notes on computer vision and pathology and hope to work together smoothly… However, they soon realize there is a rather big expertise gap – and therefore a communication gap – between the two professions. 

I experienced this divide when I started working at a digital pathology company. Brilliant programmers and bioimage analysis scientists were doing their best to develop tissue image analysis algorithms without actually understanding the tissue. When I joined I had to learn a lot about image analysis, the tools, and the strengths and limitations of different methods – including classical and deep learning image analysis approaches and the post-processing of images.

I also realized that to optimize the analysis for a particular output, I had to live with the fact that the algorithm was not always perfect in the irrelevant parts of tissue. (For a pathologist, it is a big visual discordance when tissue image analysis markups do not match the actual tissue – we are trained for years to spot things that don’t fit).

I realized that this knowledge gap was not unique to my workplace. My computer vision colleagues also needed to acquire the relevant pathology knowledge to work independently on their projects. We just needed to know enough about each other’s fields to figure out the best solution for our tissue image analysis problems. We needed a bridge. This missing bridge was a result of a siloed approach to science, combined with the highly specialized and individual nature of the professions involved in the discipline of computational pathology. So, I created a pathology training program for non-pathologists involved in tissue image analysis.

I founded my blog – The Digital Pathology Place – in 2019. Fast-forward four years, the platform has expanded to a podcast, a YouTube channel, and a series of courses. My mission is to bridge the gap between pathology and computer science, advance digital pathology, and ultimately improve patient care.

When I started my digital pathology journey, it was a bit of a lonely place, but now, the landscape looks a lot better. The recent Pathology Vision Conference organized by the Digital Pathology Association (DPA) sold out to over 800 people! The vendors are engaging in conversations with users, and the users are initiating new developments in this space. Pathologists are starting their own digital pathology companies and are an integral part of digital pathology startups. The DPA is constantly expanding and there are now five digital pathology podcasts (there were none when I started podcasting in 2019)! The digital pathology vendors are providing excellent webinars, training, and courses.

Even though collective expertise is growing, there are always more beginners. And as a community, it is our responsibility to spread knowledge and bring everyone up to speed as fast as possible. Constant communication between computer scientists and pathologists is key to maintaining a seamless digital pathology workflow. 

Newsletters

Receive the latest analytical scientist news, personalities, education, and career development – weekly to your inbox.

Newsletter Signup Image

About the Author(s)

Aleksandra Zuraw

More Articles by Aleksandra Zuraw

Explore More in Analytical Science

Dive deeper into the analytical science. Explore the latest articles, case studies, expert insights, and groundbreaking research.

False

Advertisement

Recommended

False

Related Content

Global Referral
Digital and computational pathology
Global Referral

January 12, 2024

10 min read

How digital pathology is transforming the delivery of remote second opinions

Cracking Colon Cancer
Digital and computational pathology
Cracking Colon Cancer

January 25, 2024

1 min read

How a new clinically approved AI-based tool enables rapid microsatellite instability detection

The (Pathology) IT Crowd?
Digital and computational pathology
The (Pathology) IT Crowd?

December 30, 2021

5 min read

The pathologist’s guide to IT considerations for digitization

Defining the Next Generation of NGS
Digital and computational pathology
Defining the Next Generation of NGS

December 31, 2021

1 min read

Overcoming challenges of the typical NGS workflow with the Ion Torrent™ Genexus™ System

False

The Pathologist
Subscribe

About

  • About Us
  • Work at Conexiant Europe
  • Terms and Conditions
  • Privacy Policy
  • Advertise With Us
  • Contact Us

Copyright © 2025 Texere Publishing Limited (trading as Conexiant), with registered number 08113419 whose registered office is at Booths No. 1, Booths Park, Chelford Road, Knutsford, England, WA16 8GS.