(142 days)
Sonovision is a software application intended for capturing, viewing, archiving and management of images and study data, acquired from Ultrasound machine and other similar medical imaging systems, when installed on suitable commercial standard hardware.
Sonovision is intended for use by obstetricians, gynecologists, radiologists, ultrasound technicians and cardiologists. The system is designed for use in hospitals, medical imaging labs and medical offices.
Sonovision works as Workstation Software for Ultrasound Image Acquisition, Study Management, Reporting, Sending Studies to PACS Server or Making DICOM CD/DVD.
Sonovision is an Ultrasound Imaging Solution/Ultrasound Workstation Software for images Acquisition. Study Management & Reporting.
Sonovision capture's images and video clips from Ultrasound machine and save uncompressed images along with patient information to local database.
- Saving, searching and loading Studies into secure local Database .
- Save Studies as DICOM File, Image Files(JPG, J2K, TIFF and PNG) & Ultrasound . Reports
- Send or Retrieve Studies to PACS Server over the network .
- Make DICOM CD or DICOM DVD .
- Use computer printer to print ultrasound images .
- Image Zooming, Panning, Flipping, Rotating Options .
- Add Text Annotations on Images .
- Record Video Clips and covert them into DICOM Series/frames .
Sonovision does NOT use lossy (irreversible) compression during image handling, manipulation or storage in local Database (It creates uncompressed TIFF Files). However when user converts images or series to DICOM or other Image formats(like JPG, PNG) manually then it may apply lossy (irreversible) compression on images.
All hardware used by Sonovision 2.0 (Including computer, storage drives, network interfaces, video capture cards, monitors and printers) are commercial off-the-shelf equipment
The provided text from the 510(k) Premarket Notification for Sonovision 2.0 is a summary document primarily focused on demonstrating substantial equivalence to existing predicate devices. It does not contain details about a study to prove acceptance criteria or specific performance metrics in the way typically expected for an AI/ML medical device.
The document describes Sonovision v2.0 as an ultrasound workstation software for image acquisition, review, reporting, and archiving. Its primary functions are:
- Capturing images and video clips from ultrasound machines.
- Saving, searching, and loading studies into a local database.
- Saving studies as DICOM files, image files (JPG, J2K, TIFF, PNG), and ultrasound reports.
- Sending or retrieving studies to a PACS server.
- Making DICOM CDs or DVDs.
- Printing ultrasound images.
- Image manipulation (Zooming, Panning, Flipping, Rotating, Text Annotations).
- Recording video clips and converting them into DICOM series/frames.
Since this is a software for image handling and not an AI/ML algorithm for image analysis or diagnosis, the type of "acceptance criteria" and "study" described in the prompt's questions (e.g., accuracy, sensitivity, specificity, expert consensus, MRMC studies) are not applicable to this device as presented in the 510(k) summary. The acceptance criteria for such a system would typically revolve around functional performance, data integrity, compatibility, and user interface usability, rather than diagnostic accuracy.
Therefore, the following information is not available in the provided text:
- A table of acceptance criteria and reported device performance.
- Sample size used for the test set and data provenance.
- Number of experts used to establish ground truth and their qualifications.
- Adjudication method for the test set.
- If a multi-reader multi-case (MRMC) comparative effectiveness study was done.
- If a standalone performance (algorithm only) was done.
- The type of ground truth used.
- The sample size for the training set.
- How the ground truth for the training set was established.
In summary, the provided 510(k) document for Sonovision 2.0 does not include the type of detailed performance study information typically required for AI/ML diagnostic or prognostic devices as it is an image processing and management system, not a diagnostic algorithm. The "substantial equivalence" demonstration relies on comparing its features and intended use to legally marketed predicate devices, not on a clinical performance study with specific metrics like sensitivity or specificity.
§ 892.2050 Medical image management and processing system.
(a)
Identification. A medical image management and processing system is a device that provides one or more capabilities relating to the review and digital processing of medical images for the purposes of interpretation by a trained practitioner of disease detection, diagnosis, or patient management. The software components may provide advanced or complex image processing functions for image manipulation, enhancement, or quantification that are intended for use in the interpretation and analysis of medical images. Advanced image manipulation functions may include image segmentation, multimodality image registration, or 3D visualization. Complex quantitative functions may include semi-automated measurements or time-series measurements.(b)
Classification. Class II (special controls; voluntary standards—Digital Imaging and Communications in Medicine (DICOM) Std., Joint Photographic Experts Group (JPEG) Std., Society of Motion Picture and Television Engineers (SMPTE) Test Pattern).