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Deep learning-powered medical image segmentation

 

Data and AI are reshaping the world. Deep learning is able to make sense of large amounts of unstructured data, such as visual contents. Automatically processing medical images is among the many applications of deep learning in healthcare.

 

This blog post describes the AI core of VERIMA, proudly engineered and trained by Flair-tech. VERIMA is a software solution that allows a surgical team to plan their surgery carefully. Its deep learning core is able to process raw CT scans and automatically identify bones, vessels and organs. Via a mixed reality visor, the resulting segmentation can be viewed and interacted with as a 3D hologram.

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Why anomaly detection is not binary classification

 

Anomaly detection refers to the problem of finding patterns in data that do not
conform to expected behavior.

—Chandola et al., Anomaly Detection: A Survey

Like a fish swimming upstream, the mouse befriending the cat and the rich giving to the poor.

But also like

  • the malicious user in your organization
  • the defecting engine you just manufactured
  • the fraudulent credit card transaction you just processed
  • the unreasonable network traffic on your servers

It seems that Anomaly Detection amounts to all but separate the good from the bad. And in fact, it is. So why not dig up the good old binary classification?

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