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I’ve just analyzed Philips’ new SmartSpeed Precise dual-AI MRI technology, and it’s a game-changer for radiology departments struggling with efficiency and staffing challenges.
Here’s why this matters right now:
The average imaging center faces a 15% radiologist shortage while demand for complex MRI studies continues to climb. Patient backlogs are stretching into weeks at many facilities.
Philips’ breakthrough directly addresses these pain points with impressive results:
• Scan times cut by up to 66% (that’s 3x faster)
• Image sharpness improved by 80%
• Complete multi-parametric whole-body exams in under 60 minutes
• Capacity for 2+ additional patients daily per scanner
What makes this technology unique is the dual-AI approach – one AI engine accelerates acquisition while another simultaneously enhances image quality. Previous solutions typically sacrificed one for the other.
The impact on workflow is equally impressive. The system automates up to 80% of MRI procedures with ‘zero-click’ functionality, guiding the entire process from scan initiation to report generation.
For healthcare executives, this represents a compelling ROI proposition: increased throughput without capital expenditure on additional scanners or staff. For radiologists, it means more time for complex interpretations and less burnout from routine tasks.
Particularly noteworthy is compatibility with existing systems. The SmartSpeed Precise technology can be integrated across Philips’ entire MR portfolio, including installed systems, making it accessible without requiring complete equipment replacement.
FQHCs and resource-constrained facilities should take special note: this innovation potentially transforms access to advanced diagnostics by enabling higher throughput with existing infrastructure.
The big question: Will other vendors follow with similar dual-AI approaches? Or will we see alternative innovations addressing the same challenges?
What efficiency bottlenecks do you see in your imaging workflows that AI might solve? I’d welcome your thoughts in the comments.
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Author:
CEO/Co-Founder @ Oatmeal Health | AI Lung Cancer Screening | Almost Became a Doctor | Engineer | Follow to Share What I’ve Learned Along the Way
I help patients get the care they need earlier, preventing late-stage cancer.
That’s been the throughline across three companies and almost 20 years in healthcare. At ReferralMD, we fixed broken referral networks so patients didn’t fall through the cracks. At Oatmeal Health, it’s lung cancer: building the diagnostic and screening infrastructure so the 85% of cases caught too late get caught early instead.
Today as CEO of Oatmeal Health, I lead a team embedding AI into radiology workflows to turn routine lung CT scans into reimbursable cancer risk assessments. We partner with FQHCs to reach underserved communities, and with health systems and payers to make early detection economically sustainable. Think HeartFlow or Cleerly, but for lungs.
Between companies, I advised at Techstars and Plug and Play, mentoring founders building in digital health. That experience shaped how I think about what separates companies that ship from companies that stall: distribution, reimbursement, and clinical trust, not just technology.
I’m a CancerX alumnus, a 3x healthcare founder, and someone who believes the biggest problems in cancer aren’t scientific. They’re operational.
We’re hiring mission-driven builders at Oatmeal Health. If you want to work on something that matters, reach out.
When I’m not working, I’m traveling, mentoring, and keeping up with one very energetic husky. 🐾
Substack – The Oatmeal Bite:
Millions of patients get less care because of who they are, where they live, or how they look. I’m fighting to change that. CEO @OatmealHealth, a startup built for the underserved. The Oatmeal Bite: intel for clinicians, investors, and advocates.
Jonathan Govette
CEO of Oatmeal Health
Substack:
https://oatmealhealthjonathangovette.substack.com/
