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Tag: Radiology

What Digital Pathology can learn from Radiology

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.

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The promise of AI in medical imaging: improving medical practice

In our lab of Quantitative Imaging and Artificial Intelligence, we’re developing AI applications in a variety of areas, such as radiology and pathology. The goal is to develop applications that meet unmet medical needs, particularly in relation to precision medicine and clinical prediction.

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Software and Systems for Digital Pathology

Presented at the 4th Digital Pathology Congress, these 3 sets of slides on software and systems for digital pathology are available. Feel free to download and share with your colleagues.

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