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Sonio Suspect is intended to assist interpreting physicians, during or after fetal ultrasound examinations, by automatically identifying and characterizing abnormal fetal ultrasound findings on detected views, using machine learning techniques. The device is intended for use as a concurrent reading aid on acquired images, during and/or after fetal ultrasound examinations. The device provides information on abnormal findings that may be useful in rendering potential diagnosis. Patient management decisions should not be made solely on the results of the Sonio Suspect analysis.

Sonio Suspect is a Software as a Service (SaaS) solution that aims at helping interpreting physicians (designated as healthcare professionals i.e. HCP in the following) to identify abnormal fetal ultrasound findings during and/or after fetal ultrasound examinations. Sonio Suspect is a web application accessible from any device connected to the internet. It can be accessed on a tablet, computer or any other support capable of providing access to a web application. Sonio Suspect can be used by HCPs as a concurrent reading aid on acquired images, to assist them during and/or after fetal ultrasound examinations of gestational age (GA): from 11 weeks to 41 weeks. A concurrent read by the users means a read in which the device output is available during and/or after the fetal ultrasound examination. The way Sonio Suspect is built allows the HCP to use it at any moment. The software can process any Ultrasound image file uploaded by the HCP, at any time. Sonio Suspect can be connected through API to external devices (as an ultrasound machine) to receive images. Sonio Suspect workflow goes through the following steps: As soon as an image is automatically received, it is automatically detected and associated with a view (and can be manually re-associated by the HCP). Then abnormal fetal ultrasound findings linked to the view are evaluated and displayed, individually, with one of the following status: - Suspected (abnormal findings identified on the image); - . Not Suspected (abnormal findings not identified on the image); - . Can't be analyzed (abnormal findings not evaluated due to one or several structures not detected or if the fetal position selected is "other or unknown" while it's required to evaluate the abnormal finding). Each abnormal finding status can be manually overridden to Present or Not Present by the user.

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 Software as a Service SaaS solution that aims at helping sonographers, OB/GYN MFMs and Fetal surgeons (all three designated as healthcare professionals i.e. HCP in the following) to perform their routine fetal ultrasound examinations in real-time. Sonio Detect can be used by Healthcare Professionals HCPs during fetal ultrasound exams for Trimester 1, Trimester 2 and Trimester 3 of the fetus (GA: from 11 weeks to 37 weeks). The software is intended to assist HCPs in assuring during and after their examination that the examination is complete and all images were collected according to their protocol. Sonio Detect requires the following: - Edge Software (described below) to install on a server on the same network as the ● Ultrasound Machine; - . SaaS accessibility from any internet browser (recommended browser: Google Chrome). Sonio's Edge Software is a light-weight application that runs on a server (computer) connected to the same network as the Ultrasound Machine. Sonio Edge Software is installed on the HCP server (computer) and network and the main purpose is to receive DICOM instances from the Ultrasound Machine and upload them to Sonio's Cloud to be used by Sonio Detect. Sonio Detect receives fetal ultrasound images and clips from the ultrasound machine, that are submitted through the edge software by the performing healthcare professional, in real-time and performs the following: - Automatically detect views; ● - Automatically detect anatomical structures within the supported views; . - Automatically verify quality criteria and characteristics of the supported views by checking whether they conform to standardized quality criteria Quality criteria are related to: - The presence of an anatomical structure; ● - . The absence of an anatomical structure: Characteristics are related to other items than quality criteria: - . Location of the placenta - . Fetus sex Sonio Detect then automatically associates the image to its detected view. It also highlights in yellow the view and/or the corresponding quality criteria or characteristics if there are unverified items: quality criteria or characteristics not verified or view not detected. The end user can interact with the software to override the Sonio Detect's outputs (reassign the image to another view or unassign it or assign it if it was not assigned, changes the status of a quality criteria from verified to unverified or from unverified to verified) and manually set the characteristics of the views. The user has the ability to review and edit/override the matching at any time during or at the end of the exam.

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 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 Software as a Service SaaS solution that aims at helping sonographers, OB/GYNs, MFMs and Fetal surgeons (all three designated as healthcare professionals i.e. HCP) to perform their routine fetal ultrasound examinations in real-time. Sonio Detect can be used by Healthcare Professionals HCPs during fetal ultrasound exams for Trimester 1, Trimester 2 and Trimester 3 of the fetus (Gestational Age: from 11 weeks to 37 weeks). The software is intended to assist HCPs in assuring during and after their examination that the examination is complete and all images were collected according to their protocol. Sonio Detect receives fetal ultrasound images and clips from the ultrasound machine, that are submitted through the edge software by the performing healthcare professional, in real-time and performs the following: - . Automatically detect views; - Automatically detect anatomical structures within the supported views; . - Automatically verify quality criteria of the supported views by checking whether they . conform to standardized quality criteria. Quality criteria are related to: - the presence or absence of an anatomical structure; ● - the zoom level for some views. Sonio Detect then automatically associates the image to its detected view. It also highlights in yellow the view and/or the corresponding quality criteria if there are unverified items : quality criteria not verified or view not detected. The end user can interact with the software to override the Sonio Detect's outputs (reassign the image to another view or unassign it or assign it if it was not assigned, change the status of a quality criteria from verified to unverified or from unverified to verified). The user has the ability to review and edit/override the matching at any time during or at the end of the exam.