Skip to content
  • Our Work
    • Fields
      • Cardiology
      • ENT
      • Gastro
      • Orthopedics
      • Ophthalmology
      • Pulmonology
      • Surgical Intelligence
      • Surgical Robotics
      • Urology
      • Other
    • Modalities
      • Endoscopy
      • Medical Segmentation
      • Microscopy
      • Ultrasound
  • Success Stories
  • Insights
    • Magazine
    • Upcoming Events
    • Webinars
    • Meetups
    • News
    • Blog
  • The company
    • About us
    • Careers
Menu
  • Our Work
    • Fields
      • Cardiology
      • ENT
      • Gastro
      • Orthopedics
      • Ophthalmology
      • Pulmonology
      • Surgical Intelligence
      • Surgical Robotics
      • Urology
      • Other
    • Modalities
      • Endoscopy
      • Medical Segmentation
      • Microscopy
      • Ultrasound
  • Success Stories
  • Insights
    • Magazine
    • Upcoming Events
    • Webinars
    • Meetups
    • News
    • Blog
  • The company
    • About us
    • Careers
Contact

Cardiology

Driving innovation across cardiac imaging modalities

RSIP Vision brings broad and deep experience to the table for developing novel image analysis solutions for cardiology. We've executed successful cardiac image analysis projects in all the relevant imaging modalities-CT, MRI, fluoro, ultrasound, point cloud-and powered product development efforts in a wide variety of computer vision use cases in the field.

AI and Computer Vision Technologies

Much more than AI, we integrate expert medical knowledge from Day One, and leverage all image analysis techniques – from neural networks to 3D computer vision to parametric modeling, integrating multiple data sources and expert clinical knowledge to power the solution.

Anatomical segregation and precise measurements

+
Contrast CT Segmentation
  • Anatomical segregation and precise measurements
  • Parition of adjacent cardiac chambers, vasculature and surrounding mediastinal structures
  • Extraction of pertinent radiological findings in accordance with physician's request 
  • Post-processing and custom measurements of complex anatomical and pathological findings
  • Customizable for all cardiovascular applications

2D to 3D Reconstruction​

Reconstruct catheters, guidewires, and anatomy in 3D

+
3D Reconstruction​
Medically accurate 3D rendering of the heart

Applications

  • 3D reconstruction of cardiac chambers, great vessels & coronary arteries from 2D images
  • 3D reconsruction of guidewires/catheters/delivery systems within complex anatomry

Input types

  • Fluoroscopy/Angiography, TTE, TEE, ICE, CT, MRI

Technologies

  • Neural networks - when training data is available
  • Classical computer vision

Multimodal Registration

Match 2D imaging to 3D anatomy

+
Multimodal Registration​
  • Classical & deep learning based technologies
  • Customized to user needs
  • 2D to 2D, 2D to 3D, and 3D to 3D capabilities
  • Rigid and deformable registration
  • Support all modalities & image characteristics

IVUS

Characterization of coronary artery lumen and atherosclerotic plaques

+
IVUS
  • Deep-learning based analysis
  • Intravascular Imaging System enhancement
  • Automated segmentation of cross-sectional measurements
  • Automatic measurement of coronary artery lumen
  • Lesions characterization
  • Auto analysis of narrowing of the arteries including degree of calcification
  • Real-time depiction provides immediate feedback to the physician during the procedure
  • Enhanced artifact elimination
Cardiac MRI Heart Chambers Segmentation

MRI Segmentation

Deliniation of cardiac structures by dynamic and static imaging

+
MRI Segmentation
  • Cardiac MRI Heart Chambers SegmentationDelineation of cardiac structures by static and dynamic imaging
  • Customizable for all cardiovascular applications
  • Superior soft tissue assessment
  • Physiological characterization of myocardial and valvular diseases (e.g. stenosis & regurgitation) by post-processing and custom measurements
Intravenous OCT

IVOCT

High-resolution depiction of Coronary artery intraluminal morhology

+
IVOCT
  • Intravenous OCTDeep-learning based analysis
  • Automatic measurement of coronary artery lumen
  • Coronary artery wall and luminal abnormality detection
  • Real-time depiction  provides immediate feedback to the interventional cardiologist during the procedure
  • Enhanced artifact elimination
  • IVUS – IVOCT fusion

Case study

3D Reconstruction for Heart Chambers

The challenge
  • An industry leaders in the electrophysiology space want to develop innovative solutions for improved mapping of electrical activity and anatomy of heart chambers
  • The goal was to create faster and more informative maps from noisy and sparse data
  • Developing these unique capabilities would enable the organization to gain a competitive edge
Our approach
  • The RSIP Vision R&D teams developed production – quality mathematical models, algorithms, and software implementations, providing unique and effective capabilities for the mapping tasks
  • We developed the initial client IP seeds into fully functional implementation
  • We created a new IP on behalf of the client by inventing novel models from the ground up
The outcome
Electrical activity mapping:
  • Is now integrated & in clinical use in industry-leading medical device
  • Provides unique insights for evaluation of complex pathologies
  • Has generated excellent physician feedback and is a  significant market differentiator for our client
3D anatomical reconstruction:
  • Proven in >100 clinical trial cases
  • Producing anatomically accurate maps from sparse and noisy input
  • Reduces mapping time by up to 15 minutes

Learn more

Learn more solutions and technologies from this field

PR – Non-Invasive Planning of Coronary Intervention

RSIP Vision Presents New Technology for Non-Invasive Planning of Coronary Intervention Innovative technology provides accurate coronary artery 3D reconstruction from 2D angiography to be used for diagnosis, measurements, stent modelling, and characterization for procedural planning. TEL AVIV, Israel & SAN JOSE, Calif., December 8, 2021 – RSIP Vision, an experienced leader in driving innovation for medical imaging through advanced AI and computer vision solutions, today announces a new coronary artery modelling technology. This technology enables quick and accurate reconstruction of the coronary vasculature during angiography into a 3D model. This

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

AI in Cardiac CT angiography

Coronary computed tomography angiography (CCTA) is an efficient and non-invasive imaging modality with widespread clinical implementation in the identification of coronary artery disease (CAD). With rapid 3D visualization of coronary arteries and heart, including visualization of blood flow in arteries and capillaries, CCTA enables accurate monitoring of the coronary tree for blockages and other pathologies, yet, some major challenges remain to be met to maximize its clinical value. Complexity of CCTA Analysis: diagnostic accuracy of CCTA. The diagnostic value of CCTA relies on manual assessment of a 3D model of

Read More

Coronary Arteries Segmentation

Coronary artery disease (CAD) or ischemic heart disease (IHD) has become one of the most common causes of morbidity and mortality worldwide. Patients who suffer from CAD, usually have accumulation of deposits such as lipids and inflammatory cells within the coronary arteries, potentially causing abnormal blood flow to the heart muscle due to vessel stenosis, causing ischemia and permanent damage to the heart. Sometimes, a sudden plaque rupture occurs within the coronary artery resulting in acute coronary syndromes (ACS). In these life-threatening cases, also referred to as myocardial infarction (MI)

Read More

Great Vessels Segmentation with Deep Learning

The great vessels conduct blood to and from the heart. These vessels include the aorta, superior and inferior vena cava, pulmonary arteries and pulmonary veins. Since the great vessels are an integral part of systemic and pulmonary circulation, vascular pathologies involving said vessels might be deadly. Computed tomography (CT) imaging is a useful tool for assessing the great vessels, and has become an essential tool for diagnosis of vascular pathologies, including aortic arch aneurysm, valvular heart disease and congenital vascular anomalies, such as aortic stenosis, coarctation of aorta or transposition

Read More
Cardiac Motion Correction

Deep Learning in Cardiology

1.1 Segmentation tasks [10] suggest a new fully convolutional network architecture for the task of cardiovascular MRI segmentation. The architecture is based on the idea of network blocks in which each layer is densely connected with auxiliary side paths (skip connections) to all the following layers in the block. The main advantage in the structure is the reduced number of parameters, which makes training and prediction more efficient than standard CNNs. Parameter reduction is especially important in volumetric data, where the number of voxels scale cubically with the resolution and

Read More

PR – Non-Invasive Planning of Coronary Intervention

RSIP Vision Presents New Technology for Non-Invasive Planning of Coronary Intervention Innovative technology provides accurate coronary artery 3D reconstruction from 2D angiography to be used for diagnosis, measurements, stent modelling, and characterization for procedural planning. TEL AVIV, Israel & SAN JOSE, Calif., December 8, 2021 – RSIP Vision, an experienced leader in driving innovation for medical imaging through advanced AI and computer vision solutions, today announces a new coronary artery modelling technology. This technology enables quick and accurate reconstruction of the coronary vasculature during angiography into a 3D model. This

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

AI in Cardiac CT angiography

Coronary computed tomography angiography (CCTA) is an efficient and non-invasive imaging modality with widespread clinical implementation in the identification of coronary artery disease (CAD). With rapid 3D visualization of coronary arteries and heart, including visualization of blood flow in arteries and capillaries, CCTA enables accurate monitoring of the coronary tree for blockages and other pathologies, yet, some major challenges remain to be met to maximize its clinical value. Complexity of CCTA Analysis: diagnostic accuracy of CCTA. The diagnostic value of CCTA relies on manual assessment of a 3D model of

Read More

Coronary Arteries Segmentation

Coronary artery disease (CAD) or ischemic heart disease (IHD) has become one of the most common causes of morbidity and mortality worldwide. Patients who suffer from CAD, usually have accumulation of deposits such as lipids and inflammatory cells within the coronary arteries, potentially causing abnormal blood flow to the heart muscle due to vessel stenosis, causing ischemia and permanent damage to the heart. Sometimes, a sudden plaque rupture occurs within the coronary artery resulting in acute coronary syndromes (ACS). In these life-threatening cases, also referred to as myocardial infarction (MI)

Read More

Great Vessels Segmentation with Deep Learning

The great vessels conduct blood to and from the heart. These vessels include the aorta, superior and inferior vena cava, pulmonary arteries and pulmonary veins. Since the great vessels are an integral part of systemic and pulmonary circulation, vascular pathologies involving said vessels might be deadly. Computed tomography (CT) imaging is a useful tool for assessing the great vessels, and has become an essential tool for diagnosis of vascular pathologies, including aortic arch aneurysm, valvular heart disease and congenital vascular anomalies, such as aortic stenosis, coarctation of aorta or transposition

Read More
Cardiac Motion Correction

Deep Learning in Cardiology

1.1 Segmentation tasks [10] suggest a new fully convolutional network architecture for the task of cardiovascular MRI segmentation. The architecture is based on the idea of network blocks in which each layer is densely connected with auxiliary side paths (skip connections) to all the following layers in the block. The main advantage in the structure is the reduced number of parameters, which makes training and prediction more efficient than standard CNNs. Parameter reduction is especially important in volumetric data, where the number of voxels scale cubically with the resolution and

Read More
Show more

Get in touch

Please fill the following form and our experts will be happy to reply to you soon

Recent News

PR – Intra-op Virtual Measurements in Laparoscopic and Robotic-Assisted Surgeries

PR – Non-Invasive Planning of Coronary Intervention

PR – Bladder Panorama Generator and Sparse Reconstruction Tool

PR – Registration Module for Orthopedic Surgery

All news
Upcoming Events
Stay informed for our next events
Subscribe to Our Magazines

Subscribe now and receive the Computer Vision News Magazine every month to your mailbox

 
Subscribe for free
Follow us
Linkedin Twitter Facebook Youtube

contact@rsipvision.com

Terms of Use

Privacy Policy

© All rights reserved to RSIP Vision 2021

Created by Shmulik

  • Our Work
    • title-1
      • Ophthalmology
      • Uncategorized
      • Ophthalmology
      • Pulmonology
      • Cardiology
      • Orthopedics
    • Title-2
      • Orthopedics
  • Success Stories
  • Insights
  • The company