Switch to digital pathology bears fruit
Posted 11th March 2022 by Nicholas Noakes
Fully digitising pathology operations has led to greater efficiency, cost savings, and quicker diagnosis for the Laboratory of Pathology East Netherlands (LabPON). The move, made six years ago, is showing measurable benefits and now, the institution is beginning to explore the potential of deep learning computational pathology algorithms, which might push the efficiency gains even further.
Prof Alexi Baidoshvili
Digital Pathology: The Next Hurdles
Posted 31st January 2022 by Nicholas Noakes
A Market on the Rise
There has clearly been a surge in interest for digital pathology adoption over the last two years
AI use in clinical diagnosis
Posted 19th February 2021 by Nicholas Noakes
Deep learning tool predicts tumour expression from whole slide images
A deep learning model to predict RNA-Seq expression of tumours from whole slide images was among the industry innovations outlined at the 7th Digital Pathology and AI Congress for Europe. Created by French-American start-up Owkin, the detail of how the company’s HE2RNA model provides virtual spatialization of gene expression was detailed to online delegates by senior translational scientist Alberto Romagnoni who highlighted its use in clinical diagnosis. During his presentation, delegates heard how Owkin has collaborated with doctors, hospitals and academic institutions to develop the tool.
Machine learning advances diagnostics and prognostics
Posted 10th February 2021 by Nicholas Noakes
Computerized image analysis can predict cancer outcomes
The advent of digital pathology is offering a unique opportunity to develop computerized image analysis methods to diagnose disease and predict outcomes for cancer patients from histopathology tissue sections. Such advances can help predict the risk of recurrence, disease aggressiveness and long-term survival, according to a leading expert in the field, Professor Anant Madabhushi from Case Western Reserve University in Ohio.
Deep Neural Networks in image processing, predictive modelling and diagnostic decisions
Posted 2nd September 2020 by Liv Sewell
Now more than ever intelligent human beings are needed to fulfil high value and high complexity tasks and histopathology is no exception. In fact, it is one of the sectors in the most desperate need.
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.
ctDNA and AI are the way forward in early cancer detection and metastatic treatment
Posted 24th June 2020 by Joshua Sewell
We spoke with Dr David Guttery about his pioneering work using circulating tumour DNA to enable early detection, monitoring and therapeutic decision making for better patient outcomes in gynaecological cancers.
Digital pathology: From over-promising to a reality check
Posted 17th June 2020 by Liv Sewell
Almost five years ago, the plan to implement a wide-ranging digital pathology approach across the Netherlands began to take shape. As more labs across the country acquire digital pathology capability, with steps to create a strong and accessible image repository and a national image exchange platform, one of the project leaders, Professor Katrien Grünberg, offered an update and spoke of some challenges that still lie ahead.