Sonio Detect is an AI-powered software designed to assist healthcare professionals during fetal ultrasound exams by automatically identifying various fetal anatomical views and structures, and verifying the quality and characteristics of these images in real-time. This helps ensure that ultrasound examinations are complete and meet established protocols, potentially improving accuracy and efficiency in prenatal care.
Sonio Detect is intended to analyze fetal ultrasound images and clips using machine learning techniques to automatically detect views, detect anatomical structures within the views and verify quality criteria and characteristics of the views. The device is intended for use as a concurrent reading aid during the acquisition and interpretation of fetal ultrasound images.
Sonio Detect is a cloud-based Software as a Service (SaaS) solution that works with an Edge Software installed on a local server to receive DICOM images from ultrasound machines, upload them to the cloud, and uses AI algorithms to automatically detect views, anatomical structures, and verify quality criteria and characteristics in real-time. It supports images from ultrasound systems made by GE Medical, Samsung, Canon, and Philips.
Performance testing included standalone validation on a large independent dataset of 36,769 fetal ultrasound images, demonstrating high sensitivity and specificity for detecting various fetal ultrasound views, anatomical structures, and characteristics. Software verification and validation followed FDA guidance including risk analysis, design reviews, and cybersecurity testing. No clinical study was deemed necessary.
No predicate devices specified
Submission
2/9/2024
FDA Approval
4/26/2024
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