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

Point and surface registration in orthopedics

Orthopedic surgery is a branch of surgery concerned with treating the musculoskeletal system’s injuries and reconstruction. About half the population above the age of 50 suffer from some degree of osteoarthritis. According to the 2008 report of the American Academy of Orthopedic Surgery, the most common specialty among orthopedic practitioners (reporting more than one specialty) are adult knee (34%), arthroscopy (34%) sport and medicine (33%), total joint (28%), shoulder (25%) and adult hip (24%). Orthopedic surgeons practice an average of 32 orthopedic procedures per month. With growing population needs, a shortage of practitioners is expected in the next few years.
Hip replacement surgery measurements
Hip replacement surgery measurements

The work load can be reduced by introducing an accurate efficient aid for each procedure, relieving the time burden in surgery planning and performance. Emerging technologies have completely altered the course of orthopedic surgery planning, simulation, and performance. Orthopedic surgeons can now benefit from the use of a mature set of computer vision tools for patient-specific measurement, navigation, surgical simulation, surface reconstruction, and implant design. Bringing point and surface registration in the field of orthopedics, computer vision and image processing hold the potential to improve surgical practices and affect surgery outcome to favor the benefit of patients and fast recovery.

Semi-automated registration in orthopedics

Oftentimes a surgeon is required to register between a patient’s bone to a pre-operative bone or implant model. This can be performed by marking corresponding areas in both. In a common scenario, the surgeon chooses well-defined locations on both bone and model. These fiducial points are either mechanically or optically marked to be able to deduce the rigid transformation needed for registration.

Measurement accuracy being a strict constraint to registration algorithms. As a matter of fact these algorithms are expected to operate for total knee replacement within less than 1 mm accuracy. Many registration algorithms have been proposed to meet the accuracy restriction for a given imaging modality (MRI, CT or ultrasound) and have been incorporated into routine surgery planning procedures.

Measurement errors in finding fiducial points can be overcome via statistical means, by which a rigid transformation is estimated based on the most probable location of fiducial markers. Once registration accuracy has been properly met, precise measurement can then follow by combination of image processing and mathematical modeling of the measured bone.

Early registration in orthopedics implemented simple paired point matching. These algorithms relied on a simple solution of a mathematical relationship between points but yielded insufficient accuracy. Coupled with surface matching, the accuracy of registration was improved. However, both techniques did not receive wide clinical acceptance. Other approaches include the calibration of (intraoperative) fluoroscopic and ultrasound images by feature and point intensity-based matching. Trade-offs for registration should include, in addition to accuracy, the feasibility of acquiring landmark points for registration in a minimally invasive and radiation-free manner.

In total knee replacement, implant design needs to reach an alignment error of less than 3 degrees. These requirements have been empirically found to prevent long-term implant wear and allow more satisfactory function. Computer-based alignment systems now address these restrictions by robust registration and accurate surface reconstruction. With advances in surface modeling and the ability to match a flexible surface model to observable fiducial points, reconstruction of an accurate surface for implant design is increasingly utilized in clinics.

A correct match between imaging modalities and the fabricated implant is crucial for the short and long-term success of orthopedic surgeries. With the increased incorporation of computer-vision and image processing techniques into the surgical planning and simulation process, the likelihood of success is on the rise. For these ends, computerized measurement tools have been constructed to perform crucial measurements. Semi or fully automated measurement tools have been constructed successfully by engineers of RSIP Vision for over two decades. At RSIP Vision, we build computer vision based tools for measurement in both medical and non-medical applications, always adhering to the strictest accuracy standards.

Share

Share on linkedin
Share on twitter
Share on facebook

Related Content

Percutaneous Nephrolithotomy

PCNL – Planning and real-time navigation

Prostate Tumor Segmentation

Implementing AI to Improve PI-RADS Scoring

RAS Navigation

Tissue Sparing in Robotic Assisted Orthopedic Surgeries

Procedural Planning in urology

Procedural Planning in Urology

C Arm X-Ray Machine Scanner

Radiation Reduction in Robotic Assisted Surgeries (RAS) Using AI

Visible spectrum color

Hyperspectral Imaging for Robotic Assisted Surgery

Percutaneous Nephrolithotomy

PCNL – Planning and real-time navigation

Prostate Tumor Segmentation

Implementing AI to Improve PI-RADS Scoring

RAS Navigation

Tissue Sparing in Robotic Assisted Orthopedic Surgeries

Procedural Planning in urology

Procedural Planning in Urology

C Arm X-Ray Machine Scanner

Radiation Reduction in Robotic Assisted Surgeries (RAS) Using AI

Visible spectrum color

Hyperspectral Imaging for Robotic Assisted Surgery

Show all

RSIP Vision

Field-tested software solutions and custom R&D, to power your next medical products with innovative AI and image analysis capabilities.

Read more about us

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