DeepEcho develops intelligent ultrasound software utilizing Artificial Intelligence and Deep Learning to assist in ultrasound video diagnosis. This technology mimics trained sonographers to help radiologists and minimally trained clinicians perform automated fetal measurements and computer-assisted diagnosis. The platform aims to improve prenatal and maternal care globally by providing fast, precise screening with over 95% accuracy.
Funding
$0 raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
UFounders
Product
Problem
In many regions, high-quality prenatal and maternal healthcare is limited by a shortage of trained sonographers and radiologists, as well as a lack of access to advanced ultrasound equipment. This scarcity can lead to delayed or inaccurate diagnoses of prenatal complications, increasing the risk of birth defects, preterm birth, and other adverse outcomes.
Solution
DeepEcho offers an AI-powered ultrasound software solution designed to automate fetal measurements and assist clinicians in ultrasound diagnosis. The software leverages deep learning algorithms to mimic the diagnostic capabilities of trained sonographers, enabling faster and more precise screening for prenatal complications. By improving the speed and accuracy of ultrasound analysis, DeepEcho aims to democratize access to quality maternal and newborn healthcare on a global scale, particularly in underserved areas. The technology is designed to be hardware-agnostic and scalable, making it suitable for mobile and remote deployment.
Target Audience
The primary target audience includes radiologists, minimally trained clinicians, and healthcare providers in regions with limited access to sonographers and advanced ultrasound equipment.
Features
- Automated fetal measurements using AI-driven image analysis
- Computer-assisted ultrasound diagnosis to aid clinicians in identifying potential issues
- Teleguidance and remote diagnosis capabilities for use in remote or underserved areas
- Fast screening capabilities, reportedly 3 to 5 times faster than traditional methods
- High diagnostic accuracy, reportedly exceeding 95% in detecting prenatal complications
- Hardware-agnostic design for compatibility with various ultrasound devices
- Scalable solution suitable for mobile and remote deployment