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.
How deep learning is transforming medical imaging: image search
Posted 29th July 2020 by Liv Sewell
Five or six years ago, I was looking for a strategic direction for the KIMIA Lab. We started with the problems. We asked, ‘What problems do we have in medical imaging?’
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: 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.
imCMS: The door to simple, cheap, reliable bio-stratification
Posted 10th June 2020 by Liv Sewell
Bringing molecular and digital pathology closer together through a more integrative approach can lead to clear advantages for diagnostic and research workflows.
Computational pathology: Heading for personalised medicine
Posted 3rd June 2020 by Liv Sewell
Computational pathology has increased applications for diagnosis, prediction of prognosis and therapy response, facilitating the movement of healthcare towards personalised medicine.
Coupled with deep learning, such tools are ever more efficient and robust within research and clinical settings.
Digital Pathology: Lagging or Leading?
Posted 4th May 2020 by Liv Sewell
When compared to traditional methods, digital pathology may seem totally superfluous, or interesting but not all that essential. And since the costs for the elegance of digital pathology solutions are not trivial in comparison to what the peddlers traditionally have offered, it is not surprising to see the adoption curve lagging. Where then is the ‘burning platform’ that can truly drive greater adoption of digital pathology?
Automatic AI-powered Tumor Budding
Posted 27th April 2020 by Liv Sewell
Tumor Budding has been shown in numerous studies to be an independent prognostic factor in colorectal cancer (CRC) for the risk of distant metastasis and, in stage II CRC, for overall survival. Fraunhofer IIS and the Institute for Pathology, University Hospital Erlangen are developing an AI system to automatically detect tumor budding in CRC patients.