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Tag: ai

How deep learning is transforming medical imaging: image search

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?’ 

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What AI Can and Can’t Do for Digital Pathology Right Now

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.

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Digital pathology: From over-promising to a reality check

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.

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imCMS: The door to simple, cheap, reliable bio-stratification

Bringing molecular and digital pathology closer together through a more integrative approach can lead to clear advantages for diagnostic and research workflows.

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Computational pathology: Heading for personalised medicine

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.

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Digital Pathology: Lagging or Leading?

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? 

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Automatic AI-powered Tumor Budding

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.

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Digital Pathology, Computational Biology, Organ Transplants, & the Future of Medicine

Both transplant outcomes and lab methods have stagnated over the last 40 years. Ishita Moghe and Professor Kim Solez comment upon the rapidly changing landscape of medical research and the potential of digital pathology for transforming patient outcomes.

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