See-Mode Breast & Thyroid

Automatically identifies and classifies nodules and lesions found in ultrasound imaging, aimed to reduce documentation and reporting time.

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Thyroid comparison

Overview

Thyroid nodules are characterized using the ACR TI-RADS and breast lesions are characterized by the BI-RADS guidelines. Following image acquisition by the ultrasound technologist, See-Mode analyzes the images, and then generates a preliminary worksheet for the ultrasound technologist to review. Worksheets along with radiologist impressions automatically flow through to PowerScribe/Fluency. See-Mode works with images captured using the standard clinical protocols for thyroid and breast ultrasound, and supports all major modality manufacturers.

See-Mode Thyroid - image

Features

  • Detection and image grouping: Automatic localization of lesion and nodule boundaries within thyroid ultrasound images, without the user having to indicate a region of interest. See-Mode can also automatically identify each annotated image in which a given lesion appears.
  • Lesion characterization: For each identified lesion, it provides a full breakdown of the lesion features using BI-RADS is provided.
  • Nodule characterization: For each identified nodule, it provides a full breakdown of the nodule features using TI-RADS is provided.
  • Worksheet generation: Provides a digital worksheet, which can be reviewed and edited by the ultrasound technologist, along with a final PDF version which can be saved to the clinic’s PACS system. The worksheet includes a findings breakdown (with accompanying images), along with a diagram illustrating the lesion locations.
  • Generates preliminary impressions which will be sent through to the radiologist reporting system. These impressions can then be reviewed/edited by the radiologist as required.
  • Follow-up examinations: Enables matching lesion images from the current examination to images captured in a previous examination. Automatically compares new and old images, and output any identified changes in size or features.

Benefits

See-Mode aims to help clinicians by:

  • Reducing repetitive and time-consuming tasks such as image analysis, measurement extraction, and report generation.
  • Leveraging advanced pattern recognition and machine learning techniques to improve diagnostic accuracy, and reduce the chance of misdiagnosis.
  • Standardizing and improving consistency and reporting across all examinations, regardless of the tech and interpreting radiologist.

Image examples

See-Mode Thyroid Findings-1
See-Mode Breast Findings-1

To find out more about this solution or any of the other 140+ applications on the Blackford Platform, please book a discovery call with our team.

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