DiA Imaging Analysis

AI-driven Ultrasound Analysis

Health Tech & Life Sciences
Acquired by Philips
Acquired Be'er Sheva Founded 2009
Total raised
$22.5M
Last: Series B 2021-08
Stage
Acquired
Founded
2009
Headcount
22
HQ
Be'er Sheva
Sector
Health Tech & Life Sciences

About

DiA is a provider of AI-powered ultrasound analysis software that solves the two main challenges ultrasound users are struggling with today: how to capture the right image and how to analyze it correctly.​ DiA’s technology is based on advanced pattern recognition, deep learning and machine learning algorithms that automatically imitate the way the human eye detects image borders and identifies motion.

LVivo Seamless is an AI-based software solution that preselects and instantly analyzes the optimal apical cardiac ultrasound views, generating Strain, EF and Right Ventricle Size and Function measurements results for all Echo lab studies. The selected views with results appear as an in-motion secondary capture on any PACS viewer. This enables clinicians to reduce the variability associated with manually selecting views and visually analyzing cardiac ultrasound images.

DiAs LVivo Toolbox is FDA cleared, CE marked, and ISO certified and is currently used by thousands of end users worldwide.

Funding history · 4 rounds · $22.5M total

2021-08
Series B $14.0M
2018-08
Series B $5.0M
2016-03
Series A $1.9M
2010-07
Seed $600K

Sectors & technology

Primary sector
Health Tech & Life Sciences
Sub-sectors
Health Tech & Life SciencesDigital HealthcareMedical Decision SupportDigital Medical Diagnostics
Technologies
Platforms & InterfacesSoftwareArtificial IntelligenceMachine LearningImage Recognition
Target customers
Healthcare & Life SciencesHealthcareProviders
Business model
B2B2CB2B

Highlights

1 Patents

Tags

image-processingcardiologyautomationsoftware-applicationsimaginghospitalsdigital-healthcareartificial-intelligencehealthcare-providersdecision-makingdata-analyticsdiagnosticsmachine-learningoptronicsmedical-technologiesimage-recognitionclinicsdecision-supportultrasound