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Medical segmentation

Why are we the best partner for medical segmentation?

Having a robust and accurate segmentation engine is the basis for the most advanced medical applications. We have years of experience developing such solutions, in all modalities (CT, MRI, X-ray, ultrasound) and clinical fields. Our solutions are clinically proven and deployed.

AI and Computer Vision Technologies

Developing advanced segmentation solutions, we use the most powerful tools from deep learning to 3D computer vision and classic analysis algorithms. We provide accurate, quick, and robust medical solutions.

Brain hemorrhage segmentation

Brain Hemorrhage, Ventricles, and Edema

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Brain Hemorrhage, Ventricles, and Edema

  • Identification and segmentation of bleeds and edema
  • Calculating volumes of bleeds and edema
  • Tracking dynamics of bleeds

All Bones Segmentation Engine

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Bones

  • X-ray and CT segmentation
  • Planning and designing custom joint implants
  • Surgical planning, including robotic surgeries
  • 3D models from 2D X-ray images
    Metal segmentation

Liver and Liver
Tumors

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Liver and Liver Tumors

  • Tumor segmentation and delineation
  • Tumor measurements: size and density
  • Tracking changes in tumor (follow-ups)

Teeth

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Teeth

  • Segmentation and classification of individual teeth
  • Multimodality - CT, MRI and X-rays
  • Jaw and nerve tunnel segmentation
  • Surgical planning

Knee

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Knee

  • X-ray and CT segmentation
  • Planning and designing custom knee implants
  • Surgical planning, including robotic surgeries
  • 3D models from 2D X-ray images
  • Metal segmentation
  • Dynamic simulation of replacement

Lung Tumors

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Lung Tumors

  • Segmentation and delineation of tumors
  • Multimodality- X-ray and CT
  • Surgical planning
  • Tracking changes in measurements (follow-ups)

Coronary Arteries

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Coronary Arteries

  • CT fluorescein angiography segmentation
  • Virtual assessment of blood flow (Fractional flow reserve)
  • Stenosis detection and assessment
  • Planning stent design and placement

Lung Nodules

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Lung Nodules

  • Segmentation and detection of small nodules
  • Surgical planning
  • Tracking changes (follow-ups)

Hip

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Hip

  • X-ray and CT segmentation
  • Planning and designing custom hip implants
  • Surgical planning, including robotic surgeries
  • 3D models from 2D X-ray images
  • Metal segmentation
  • Dynamic simulation of replacement

Mediastinal Lymph Nodes

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Mediastinal Lymph Nodes

  • Segmentation and detection of lesions
  • Biopsy planning and preparation
  • Contrast CT

Pulmonary Blood Vessels

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Pulmonary Blood Vessels

  • Accurate segmentation from contrast CT
  • Surgical planning in combination with other segmentations
  • Avoid blood vessel perforation and other complications

Pulmonary Lobes

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Pulmonary Lobes

  • Segmentation of all lobes, and lobe segments
  • Plan surgery for lobectomy
  • Avoid complications and assist navigation

Airways

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Airways

  • Baseline for bronchoscopy navigation
  • Useful when camera is no longer available (thinning of pathway)
  • In combination with other pulmonary segmentations
Lung fissures

Pulmonary Fissures

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Pulmonary Fissures

  • Segmentation of all pulmonary fissures
  • Plan RAS or bronchoscopy
  • Avoid perforations and assist navigation

Vertebrae

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Vertebrae

  • Multimodal segmentation – CT, MRI, or X-ray
  • Surgical planning in RAS, 3D printing and implant fitting
  • Baseline for AR procedures

Great Vessels
Analysis

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Great Vessels Analysis

  • Segmentation from contrast CT
  • Detect abnormalities such as aneurysms and calcifications
  • Plan catheterizations
Kidney segmentation

Renal Artery, Vein, Calyces, Ureter, Cortex, and Medulla

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Renal Artery, Vein, Calyces, Ureter, Cortex, and Medulla

  • Requires 4-phase CT with contrast and registration
  • Detection of abnormalities and tumors
  • Plan surgical removal of kidney stones or ablations

Shoulder Planning and Navigation

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Shoulder

  • Increased segmentation accuracy for adequate surgical planning
  • 3D printing for jig and implant testing
  • Metal segmentation
Sinus segmentation

Sinuses

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Sinuses

  • Suitable for CT, MRI, or cone-beam CT
  • Plan surgical ENT procedure
  • Reduce complication when opening blockages and draining fluid

Case study

Chest CT Segmentation

The challenge
  • An industry-leading medical device company required the capability to automatically generate an accurate 3D model of complex patient-specific anatomies
  • The anatomical model was needed for planning challenging surgical navigation procedures
  • The pre-existing solution was slow and not robust, requiring extensive and time-consuming manual editing by the interventionist
Our approach

  • The RSIP Vision team leveraged its deep-learning based 3D CT auto-segmentation technology to deliver a customized, fast, robust, production quality solution

The outcome
  • Our core module has been integrated into our clients platform and is in clinical use
  • Used in 1000s of cases in hospitals worldwide
  • >99% segmentation success rate
  • 1mm-level segmentation resolution
  • 30 seconds running time on full-sized chest CT scan

Learn more

Learn more solutions and technologies from this field

RAS Navigation

Tissue Sparing in Robotic Assisted Orthopedic Surgeries

Orthopedic surgeries such as hip or knee replacement are performed via an incision which often compromises the surrounding tissue. The assimilation of RAS into these surgeries significantly decreases the incision size and allows sparing of more tissue compared with standard surgeries. In addition, RAS possess higher accuracy and precision during the procedure. The combination of smaller incision, less damage to nearby tissue, and better accuracy for implant placement, results in faster recovery, lower pain levels reported, and fewer complications. Improve Procedural Planning with AI The first step towards a tissue

Read More
Intraoperative Registration Module for Orthopedic Surgery

Announcement – Registration Module for Orthopedic Surgery

RSIP Vision Announces Patient-Specific, Intraoperative Registration Module for Orthopedic Surgery The new neural network technology enables accurate, quantitative measurements of bones and implants during the surgery supporting optimization of implant positioning and improved patient outcomes. TEL AVIV, Israel & SAN JOSE, Calif., August 12, 2021 – RSIP Vision, a clinically proven leader in real-world AI solutions for medical image analysis, announced today a novel 2D to 3D registration module that will improve the execution of orthopedic surgeries, such as total hip arthroplasty. Utilizing a proprietary neural network, trained on patient-specific

Read More
Automated Assessment of Cartilage Damage

Announcement – Automated Assessment of Cartilage Damage

RSIP Vision Announces New Tool for Sports Medicine Applications, Enabling Automated Assessment of Cartilage Damage This new algorithmic software provides automated measurement of articular cartilage in MRI scans, thereby improving evaluation of the integrity and extent of damaged cartilage while elevating diagnosis, treatment and recovery care options. TEL AVIV, Israel & SAN JOSE, Calif., July 12, 2021 – RSIP Vision, a clinically proven leader in real-world AI solutions for medical image analysis, announced today a new articular cartilage segmentation tool that delivers accurate, non-invasive and automatic assessment of chondral lesions

Read More
one-click segmentation

One-click segmentation of medical images

In the medical field, image analysis plays a crucial role in both diagnosis and treatment. Its central tool is segmentation, which involves partitioning an image into multiple meaningful segments for future analysis and use. Medical image segmentation presents many challenges: Large number of different modalities (X-ray, ultrasound, CT, MRI and many more). Detection of the region of interest, which varies depending on the task at hand. Tedious and lengthy human work, which often requires uncommon expertise. Automation levels in segmentation A range of automation levels can be used in order

Read More
Liver and tumors

Liver Tumor Segmentation with Deep Learning

Liver tumors, also known as hepatic tumors, are quite common and some poses a grim prognosis. Therefore, early detection and diagnosis has become a main goal for lowering mortality and morbidity. Benign tumors include hemangiomas, adenomas, focal nodular hyperplasia (FNH). Although malignant tumors that are found in the liver are metastases of malignancies in other location, primary liver cancer is the sixth most common cancer worldwide, both in developing and industrialized countries. Prognosis is usually poor, with low survival rates. The most common primary malignant tumor is hepatocellular carcinoma (HCC),

Read More
lymph nodes

Lymph Node Segmentation Module

Lymph nodes are routinely examined and assessed during physical examination of patients in a clinic or hospital setting. Enlarged lymph nodes can be indicators of infection, cancer and other pathologies. Therefore, a biopsy of a suspected lymph node, which provides tissue histology or cytology is a vital step towards diagnosis. In relation to malignancy, initial staging before treatment is done using the Ann Arbor staging system or Lugano classification, by analyzing patient’s computed tomography (CT) and positron emission tomography (PET) scans. In addition, tracking the changes in lymph node’s size,

Read More
RAS Navigation

Tissue Sparing in Robotic Assisted Orthopedic Surgeries

Orthopedic surgeries such as hip or knee replacement are performed via an incision which often compromises the surrounding tissue. The assimilation of RAS into these surgeries significantly decreases the incision size and allows sparing of more tissue compared with standard surgeries. In addition, RAS possess higher accuracy and precision during the procedure. The combination of smaller incision, less damage to nearby tissue, and better accuracy for implant placement, results in faster recovery, lower pain levels reported, and fewer complications. Improve Procedural Planning with AI The first step towards a tissue

Read More
Intraoperative Registration Module for Orthopedic Surgery

Announcement – Registration Module for Orthopedic Surgery

RSIP Vision Announces Patient-Specific, Intraoperative Registration Module for Orthopedic Surgery The new neural network technology enables accurate, quantitative measurements of bones and implants during the surgery supporting optimization of implant positioning and improved patient outcomes. TEL AVIV, Israel & SAN JOSE, Calif., August 12, 2021 – RSIP Vision, a clinically proven leader in real-world AI solutions for medical image analysis, announced today a novel 2D to 3D registration module that will improve the execution of orthopedic surgeries, such as total hip arthroplasty. Utilizing a proprietary neural network, trained on patient-specific

Read More
Automated Assessment of Cartilage Damage

Announcement – Automated Assessment of Cartilage Damage

RSIP Vision Announces New Tool for Sports Medicine Applications, Enabling Automated Assessment of Cartilage Damage This new algorithmic software provides automated measurement of articular cartilage in MRI scans, thereby improving evaluation of the integrity and extent of damaged cartilage while elevating diagnosis, treatment and recovery care options. TEL AVIV, Israel & SAN JOSE, Calif., July 12, 2021 – RSIP Vision, a clinically proven leader in real-world AI solutions for medical image analysis, announced today a new articular cartilage segmentation tool that delivers accurate, non-invasive and automatic assessment of chondral lesions

Read More
one-click segmentation

One-click segmentation of medical images

In the medical field, image analysis plays a crucial role in both diagnosis and treatment. Its central tool is segmentation, which involves partitioning an image into multiple meaningful segments for future analysis and use. Medical image segmentation presents many challenges: Large number of different modalities (X-ray, ultrasound, CT, MRI and many more). Detection of the region of interest, which varies depending on the task at hand. Tedious and lengthy human work, which often requires uncommon expertise. Automation levels in segmentation A range of automation levels can be used in order

Read More
Liver and tumors

Liver Tumor Segmentation with Deep Learning

Liver tumors, also known as hepatic tumors, are quite common and some poses a grim prognosis. Therefore, early detection and diagnosis has become a main goal for lowering mortality and morbidity. Benign tumors include hemangiomas, adenomas, focal nodular hyperplasia (FNH). Although malignant tumors that are found in the liver are metastases of malignancies in other location, primary liver cancer is the sixth most common cancer worldwide, both in developing and industrialized countries. Prognosis is usually poor, with low survival rates. The most common primary malignant tumor is hepatocellular carcinoma (HCC),

Read More
lymph nodes

Lymph Node Segmentation Module

Lymph nodes are routinely examined and assessed during physical examination of patients in a clinic or hospital setting. Enlarged lymph nodes can be indicators of infection, cancer and other pathologies. Therefore, a biopsy of a suspected lymph node, which provides tissue histology or cytology is a vital step towards diagnosis. In relation to malignancy, initial staging before treatment is done using the Ann Arbor staging system or Lugano classification, by analyzing patient’s computed tomography (CT) and positron emission tomography (PET) scans. In addition, tracking the changes in lymph node’s size,

Read More
Show more

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