What AI Can and Can’t Do for Digital Pathology Right Now
Posted 15th July 2020 by Liv Sewell
It was fascinating to speak with Hamid Tizhoosh, Professor at the Faculty of Engineering at the University of Waterloo in Canada, Director of KIMIA Lab and keynote speaker at the 6th Digital Pathology & AI Congress: USA, about using AI to transform what is possible in medical imaging.
Digital Pathology in Drug Development: Opportunities and Challenges
Posted 20th April 2020 by Liv Sewell
We recently caught up with Dr Olulanu Aina, Scientific Director and Veterinary and Toxicological Pathologist at Janssen, about digital pathology applications in drug discovery...
Unleashing the power of digital pathology and AI for precision medicine
Posted 2nd October 2019 by Joshua Sewell
We’re looking back at the highlights from the Digital Pathology and AI meeting in 2018 as we anticipate this year’s Digital Pathology and AI Congress in December. This second post in our mini-series reviews Marylin Bui’s keynote presentation where she explained how the combination of Digital Pathology and Artificial Intelligence (AI) holds huge potential for patient care.
A High impact Open-Source tool for Digital Pathology Quality Control
Posted 11th September 2019 by Joshua Sewell
Ahead of his presentation at the 6th Digital Pathology and AI Congress: Europe, we spoke to Andrew Janowczyk about his work creating scalable data analysis techniques to facilitate cancer research through the development of open-source Digital Pathology tools.
What Digital Pathology can learn from Radiology
Posted 17th May 2019 by Joshua Sewell
Radiology is ahead of the curve because they’ve had CAD (Computer Aided Detection) for about 20 years. Radiology as a field has therefore had experience of introducing and integrating AI algorithms.
In my previous post, I talked about high-level cross imaging modalities. Here, I will discuss three challenges specific to pathology. I also work with Radiology imaging, and I think that comparisons between the two can help see how pathology might develop in the future.
Transforming medical image analysis with deep learning AI
Posted 5th April 2019 by Joshua Sewell
Aiforia Technologies is a medical AI software company seeking to transform clinical pathology and medical research by bringing deep learning AI to assist and augment human experts in medical image analysis.
We had the chance to ask CEO Kaisa Helminen about AI in healthcare and Aiforia’s newest platform.
Quantitative Image Analysis Guidelines: An Open letter from Liron Pantanowitz
Posted 20th October 2017 by Jane Williams
Dear Colleagues,
There has been a steady increase in the adoption of Quantitative Image Analysis (QIA) for diagnostic purposes, especially for breast biomarker testing.
