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DrAid™ for Liver Segmentation is a web-based software, non-invasive image analysis application designed for the visualization, evaluation, and reporting of liver and physician identified lesions using multiphase images (with slice thickness <= 3.0mm) of patients aged and older than 22 years old obtained from CT scanners. The software provides a range of tools for image viewing, processing, and reporting. The software enables professionals, including physicians and technicians, to review and analyze multiphase volume datasets of the liver. DrAid™ for Liver Segmentation operates in a semautomated quantitative imaging function, utilizing an Al algorithm to generate liver segmentation that is then editable by the physician if necessary. Additionally, the device provides tools for manual segmentation within user input of seed points and boundary editing for physician-identified lesions within the liver. Professionals can assess liver volume (mm³), liver lesion volume (mm³), and maximum lesion diameter (mm), position, thereby aiding in evaluation and treatment planning. It is important to note that the software is intended for use by trained professionals. including physicians and technicians. The image source for analysis is DICOM, allowing compatibility with standard medical imaging data formats. Note: DrAid™ for Liver Segmentation does not generate diagnoses or potential findings directly. The interpretation of the image data and the clinical decision-making process should be performed by qualified healthicare professionals. The installation and deployment of the software medical device should be carried out by VinBrain and trained technicians. Caution: Federal law restricts this device to sale by or on the order of a physician.

DrAid™ for Liver Segmentation is a web-based software that processes and analyzes multiphase CT images in DICOM format. The software utilizes AI algorithms for semi-automated liver segmentation, combined with manual editing capabilities. Additionally, the device provides tools for manual segmentation with user input of seed points and boundary editing for physician-identified lesions within the liver. Key device components: - AI algorithm for liver segmentation - Measurement algorithm - DICOM Processing Module for CT images - Liver Segmentation viewer - Results Export Module - Device Characteristics: - Software Environment of Use: - Healthcare facility/hospital Key Features for SE/Performance: - Visualization modes: - Original DICOM 2D image viewing - -MPR visualization - -Manual correction tools: - Seed point placement - Boundary editing for lesions - Segmentation refinement - Reporting tool. - Energy Source: - -Web-based application running on standard hospital/clinic workstations

The DrAid™ for Radiology v1 is a radiological computer-assisted triage & notification software to aid the clinical assessment of adult Chest X-Ray cases with features suggestive of pneumothorax in medical care environment. DrAid™ analyzes cases using an artificial intelligence algorithm to features suggestive of suspected findings. It makes case-level output available to a PACS for worklist prioritization or triage. As a passive notification for prioritization-only software tool with standard of care workflow, DrAid™ does not send a proactive alert directly to appropriately trained medical specialists. DrAid™ is not intended to direct attention to specific portions or anomalies of an image. Its results are not intended to be used on a stand-alone basis for clinical decisionmaking nor is it intended to rule out pneumothorax or otherwise preclude clinical assessment of X-Ray cases.

DrAid™ for Radiology v1 (hereafter called DrAid™ or DrAid) is a a radiological computer-assisted triage & notification software product that automatically identifies suspected pneumothorax on frontal chest x-ray images and notifies PACS of the presence of pneumothorax in the scan. This notification enables prioritized review by the appropriately trained medical specialists who are qualified to interpret chest radiographs. The software does not alter the order or remove cases from the reading queue. The device's aim is to aid in the prioritization and triage of radiological medical images only. Chest radiographs are automatically received from the user's image storage system (e.g. Picture Archiving and Communication System (PACS)) or other radiological imaging equipment (e.g. Xray systems) and processed by DrAid™ for analysis. Following receipt of chest radiographs, the software device de-identifies a copy of each chest radiographs in DICOM format (.dcm) and automatically analyzes each image to identify features suggestive of pneumothorax. Based on the analysis result, the software notifies PACS/workstation for the presence of Pneumothorax as indicating either "flag" or "(blank)". This would allow the appropriately trained medical specialists to group suspicious exams together that may potentially benefit for their prioritization. Chest radiographs without an identified anomaly are placed in the worklist for routine review, which is the current standard of care. The DrAid™ device works in parallel to and in conjunction with the standard care of workflow. After a chest x-ray has been performed, a copy of the study is automatically retrieved and processed by the DrAid™ device, therefore, the analysis result can also be provided in the form of DICOM files containing information on the presence of suspicious Pneumothorax. In parallel, the algorithms produce an on-device notification indicating which cases were prioritized by DrAid™ in PACS. The on-device notification does not provide any diagnostic information and it is not intended to inform any clinical decision, prioritization, or action to who are qualified to interpret chest radiographs. It is meant as a tool to assist in improving workload prioritization of critical cases. The final diagnosis is provided by the radiologist after reviewing the scan itself. The following modules compose the DrAid™: Data input and validation: Following retrieval of a study, the validation feature assessed the input data (e.g. age, modality, view) to ensure compatibility for processing by the algorithm. AI algorithm: Once a study has been validated, the AI algorithm analyzes the frontal chest x-ray for detection of suspected pneumothorax. API Cognitive service: The study analysis and the results of a successful study analysis are provided through an API service, to then be sent to the PACS for triaging & notification. Error codes feature: In the case of a study failure during data validation or the analysis by the algorithm, an error is provided to the system.