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More Money Pours into Medical Imaging AI Startups

We’ve updated our analysis of capital funding for startups who are developing machine learning solutions for medical image analysis to capture the latest deals. You can download the updated report for free here. So far in 2017, five start-ups have received funding, as follows:

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Investment reached a new high in Q2 2017, with the four deals worth a combined $27 million. Total investment in 2016 was $63.2 million.

Three of the deals in Q2 were notably larger than usual (average deal sizes tend to be in the region of $2.5 million), with VoxelCloud securing $10 million in Series A funding, following a $5.5 million angel funding round in September 2016. VoxelCloud is now the second most funded medical imaging AI start-up, after Zebra Medical Vision which has received $20 million in funding.

Some of the other key takeaways from our analysis are:

  • Total investment in medical imaging AI startups since 2014 is now at $167 million.
  • There are over 50 start-ups developing machine learning solutions for medical imaging. 28 of these entered the market in 2015 and 2016.
  • Around half of the total investment to date has gone to US-based startups, with Israeli start-ups accounting for around a quarter of the total.
  • In 2016, the first Chinese companies entered the market.
  • Around half of the companies are developing applications for multiple body areas. The others are focused on specific clinical specialities, e.g. pulmonology, breast, cardiovascular, etc.

With 14 new market entrants in 2016 and record investment in Q2, it seems likely that more startups will enter the market in the second half of 2017 and beyond. Q2 also saw the first exit of a medical imaging AI startup, with McCoy Medical acquired by TeraRecon – click here to see our analysis of the acquisition. With the major imaging modality and imaging IT companies strengthening their in-house AI capabilities, and with deep learning specialists a scarce resource, M&A activity looks set to ramp-up in the coming years.