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Ultrasound

Why are we an amazing partner for ultrasound processing?

Medical ultrasound is challenging and user-dependent, both in image acquisition and image analysis. Our automated technologies meet both challenges, from view recognition and volume measurements through landmarks detection and severeness classification to quality assessment acquisition guidance.

AI and Computer Vision Technologies

Our engineering and clinical teams, together with our echo specialists, leverage the most powerful tools – from deep neural networks to 3D computer vision – delivering effective, automated, and innovative solutions for diverse ultrasound use cases.

Automated Volume Measurement

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Automated FAC measurement SAX Ultrasound Echography view

  • Point Of Care Ultrasound app
  • Automatically calculating quantitative volumes  such as Fractional Area Change
  • Allows physicians to modify medical treatment accordingly
  • Multi-view in this image the Short Axis View)

Automated View Recognition and Classification

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Automated Eco view recognition and classification

    • Automated Echocardiography view recognition
    • Automated classification
    • Mitigation of user-dependent errors and bias
    • Multi-view
    • Vendor-neutral

 

Automated Quality Grading and Classification

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Automated Quality Grading and Classification

  • Automated quality grading of Echocardiographic views and image acquisition
  • Adjustable threshold and grades selection
  • Real-time quality score
  • Grading dependant on Echo guidelines

Automated Segmentation of Suspicious Area

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Automated Segmentation of Suspicious Area
  • One-click or automated segmentation of suspicious area
  • Multiple modalities and use cases

Landmark Detection & Quality Verification

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Landmark Detection & Advanced Quality Verification
  • Separate any joint including tough edge cases
  • Support noisy images, metal artifact, cone-beam
  • Detect osteophytes
  • Proven on clinical patients data
  • Accuracy at the level of scan resolution or better

Multiclass Segmentation

Automated clip analysis

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Multiclass Segmentation

  • Full Analysis of PLAX view
  • Detection and measurement of main anatomical landmarks, such as: Pericardium, RV, IVS, LVPW, LA, Mitral Valve, and Aortic valve, as well as quantification of EF and FS.
  • AI-based alerting of parameters deviating from the normal range

IVUS - Atheroma cross area measurement

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IVUS - Atheroma Cross Area Measurement

  • Intravascular Imaging System enhancement
  • Automates segmentation of cross-area measurements

ME Bicaval View Labeling

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ME Bicaval view Auto Labeling
  • Fully automatic
  • Real-time
  • Labeling of main anatomical structures, including SVC, RA, IVC, Coronary Sinus, and Inter-Atrial Septum
  • Fit for user-guided solutions
Segmented prostate gland

Prostate Ultrasound Applications

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Prostate Ultrasound Application​
Segmented prostate gland
A segmented ultrasound image of the prostate gland
  • Prostate gland segmentation
  • 3D ultrasound reconstruction for guided biopsies
  • MRI and US fusion for guided biopsies
  • Accurate placement of stents
  • Assessment of surgical necessity

Case Study

Auto-FAC & quality grading for cardiac ultrasound

The challenge
  • An innovative manufacturer of point-of-care ultrasound devices wanted to integrate unique AI capabilities
  • Users of the device are typically non-experts in ultrasound interpretation
  • Automated feedback on image quality and automated measurement of heart function in the short-axis view was required, to improve the measurement and drive better patient outcomes
Our approach
  • RSIP Vision’s multidisciplinary team of AI engineers, echo specialists, and data analysts developed & delivered production-quality AI modules
The outcome
  • Our solution is now under integration in an innovative point-of-care ultrasound device
  • The performance proved to be equivalent to a panel of human experts
  • Fully automated measurement and functional assessment
  • We are empowering users by providing real-time feedback on image acquisition quality

Learn more

Learn more solutions and technologies from this field

Ultrasound segmentation with AI

PRESS RELEASE – RSIP Vision introduces an innovative set of AI modules for enhanced medical ultrasound applications

RSIP Vision introduces an innovative set of AI modules for enhanced medical ultrasound applications. These innovative modules empower a wide range of medical applications by overcoming the main ultrasound challenges – user-dependent acquisition and noisy, clinically challenging images. This improves the workflow and diagnostic accuracy while reducing the overall procedure time. SILICON VALLEY, Calif., June 22, 2020 — RSIP Vision, a global leader in artificial intelligence (AI) and computer vision technology, announced today a new set of AI-based medical ultrasound modules. These advanced modules will serve as AI-based building blocks

Read More
Urology image fusion

Image Analysis and Artificial Intelligence in Urology

Artificial intelligence (AI) and deep learning play an increasingly crucial role in medical imaging in general, and in the field of urology particularly. The applications of AI in urology are numerous, starting with accurate diagnosis (using image segmentation and abnormality detection), continuing with biopsy and operative procedures (using tools for assisted navigation and robotic guidance), and ending in treatment assessment (using tools similar to those used in diagnosis in order to assess the response to treatment). 

Read More
Segmented prostate gland

Image Analysis and AI for BPH

Recent developments in the field of deep learning and artificial intelligence can aid in BPH detection, classification and treatment. Analyzing ultrasound and MRI images, and using deep-learning segmentation tools to process them, gives a baseline for severity classification by the physician. Follow-up scans can be accurately compared to baseline scans for optimal treatment decision. Real-time tracking, 3D image reconstruction, and fusion can all provide better guidance during stent placement and urinary tract dilation. Prostatectomy procedure can be kept within boundaries at all times.

Read More
PLAX Auto Analysis

PR – RSIP Vision Announces New Cardiac Diagnostic Tool for Point-of-Care Ultrasound Screening

New algorithmic module provides automated expert-level assessment of heart function for point-of-care medical teams enabling a quick and reliable detection of cardiac illness and heart attacks. TEL AVIV, Israel & SAN JOSE, Calif., December 15, 2020 – RSIP Vision, an experienced leader in driving innovation for medical imaging through advanced AI and computer vision solutions, today announces a new medical ultrasound module. This new software module enables medical teams at various point-of-care settings to perform a heart evaluation quickly with high accuracy and receive an immediate, onsite diagnostic from the Parasternal

Read More

Deep Learning for Cardiac Ultrasound (Echocardiography)

Despite the importance of echocardiography in the diagnosis and treatment of serious cardiac illness, this imaging technology faces two main challenges: Image quality and image assessment. RSIP Vision uses deep learning to enhance both, making it easier for physicians and researchers to interpret findings. As a result, our method resolves user variability, accuracy and efficiency in cardiac ultrasound with advanced, deep learning neural networks. Learn how we do it on our software.

Read More
Ultrasound segmentation with AI

PRESS RELEASE – RSIP Vision introduces an innovative set of AI modules for enhanced medical ultrasound applications

RSIP Vision introduces an innovative set of AI modules for enhanced medical ultrasound applications. These innovative modules empower a wide range of medical applications by overcoming the main ultrasound challenges – user-dependent acquisition and noisy, clinically challenging images. This improves the workflow and diagnostic accuracy while reducing the overall procedure time. SILICON VALLEY, Calif., June 22, 2020 — RSIP Vision, a global leader in artificial intelligence (AI) and computer vision technology, announced today a new set of AI-based medical ultrasound modules. These advanced modules will serve as AI-based building blocks

Read More
Urology image fusion

Image Analysis and Artificial Intelligence in Urology

Artificial intelligence (AI) and deep learning play an increasingly crucial role in medical imaging in general, and in the field of urology particularly. The applications of AI in urology are numerous, starting with accurate diagnosis (using image segmentation and abnormality detection), continuing with biopsy and operative procedures (using tools for assisted navigation and robotic guidance), and ending in treatment assessment (using tools similar to those used in diagnosis in order to assess the response to treatment). 

Read More
Segmented prostate gland

Image Analysis and AI for BPH

Recent developments in the field of deep learning and artificial intelligence can aid in BPH detection, classification and treatment. Analyzing ultrasound and MRI images, and using deep-learning segmentation tools to process them, gives a baseline for severity classification by the physician. Follow-up scans can be accurately compared to baseline scans for optimal treatment decision. Real-time tracking, 3D image reconstruction, and fusion can all provide better guidance during stent placement and urinary tract dilation. Prostatectomy procedure can be kept within boundaries at all times.

Read More
PLAX Auto Analysis

PR – RSIP Vision Announces New Cardiac Diagnostic Tool for Point-of-Care Ultrasound Screening

New algorithmic module provides automated expert-level assessment of heart function for point-of-care medical teams enabling a quick and reliable detection of cardiac illness and heart attacks. TEL AVIV, Israel & SAN JOSE, Calif., December 15, 2020 – RSIP Vision, an experienced leader in driving innovation for medical imaging through advanced AI and computer vision solutions, today announces a new medical ultrasound module. This new software module enables medical teams at various point-of-care settings to perform a heart evaluation quickly with high accuracy and receive an immediate, onsite diagnostic from the Parasternal

Read More

Deep Learning for Cardiac Ultrasound (Echocardiography)

Despite the importance of echocardiography in the diagnosis and treatment of serious cardiac illness, this imaging technology faces two main challenges: Image quality and image assessment. RSIP Vision uses deep learning to enhance both, making it easier for physicians and researchers to interpret findings. As a result, our method resolves user variability, accuracy and efficiency in cardiac ultrasound with advanced, deep learning neural networks. Learn how we do it on our software.

Read More
Show more

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