19 Harley St, London, W1G 9QJ, UK

Machine Learning-Based Measurement of Regional and Global Spinal Parameters Using the Concept of Incidence Angle of Inflection Points – Lumbar Fusion

Day Case Lumbar Fusion Surgery

In this article, researchers discuss the application of convolutional neural networks (CNNs) in evaluating spinal sagittal alignment. They introduce the concept of incidence angles of inflection points (IAIPs) as parameters to capture the relationship between pelvic and spinal alignment. The study analyzed whole-spine lateral radiographs from hundreds of patients using high-quality images to assess these parameters. The findings showed high success rates for certain parameters, such as pelvic and C2 incidence angles, but lower rates for sacral slope and L1 incidence. The CNN-based machine learning method achieved an impressive 80 percent detection rate for various spinal angles with a precise error threshold of 3.5°. The measurements derived from the novel formula closely aligned with those from the CNN model, demonstrating the utility of the deep learning algorithm for precise measurements of spinal sagittal parameters. Overall, the study highlights the potential for integrating machine learning with the IAIP concept to further advance our understanding of spinal health

Summarised by Mr Mo Akmal – Lead Spinal Surgeon
The London Spine Unit : top spinal hospital in UK

Published article

This study delves into the application of convolutional neural networks (CNNs) in evaluating spinal sagittal alignment, introducing the innovative concept of incidence angles of inflection points (IAIPs) as intuitive parameters to capture the interplay between pelvic and spinal alignment. Pioneering the fusion of IAIPs with machine learning for sagittal alignment analysis, this research scrutinized whole-spine lateral radiographs from hundreds of patients who visited a single institution,…

Lumbar Fusion Surgery Expert. Best Spinal Surgeon UK
Bioengineering (Basel). 2023 Oct 23;10(10):1236. doi: 10.3390/bioengineering10101236.ABSTRACTThis study delves into the application of convolutional neural networks (CNNs) in evaluating spinal sagittal alignment, introducing the innovative concept of incidence angles of inflection points (IAIPs) as intuitive parameters to capture the interplay between pelvic and spinal alignment. Pioneering the fusion of IAIPs with machine learning for sagittal,

Bioengineering (Basel). 2023 Oct 23;10(10):1236. doi: 10.3390/bioengineering10101236.

ABSTRACT

This study delves into the application of convolutional neural networks (CNNs) in evaluating spinal sagittal alignment, introducing the innovative concept of incidence angles of inflection points (IAIPs) as intuitive parameters to capture the interplay between pelvic and spinal alignment. Pioneering the fusion of IAIPs with machine learning for sagittal alignment analysis, this research scrutinized whole-spine lateral radiographs from hundreds of patients who visited a single institution, utilizing high-quality images for parameter assessments. Noteworthy findings revealed robust success rates for certain parameters, including pelvic and C2 incidence angles, but comparatively lower rates for sacral slope and L1 incidence. The proposed CNN-based machine learning method demonstrated remarkable efficiency, achieving an impressive 80 percent detection rate for various spinal angles, such as lumbar lordosis and thoracic kyphosis, with a precise error threshold of 3.5°. Further bolstering the study’s credibility, measurements derived from the novel formula closely aligned with those directly extracted from the CNN model. In , this research underscores the utility of the CNN-based deep learning algorithm in delivering precise measurements of spinal sagittal parameters, and highlights the potential for integrating machine learning with the IAIP concept for comprehensive data accumulation in the domain of sagittal spinal alignment analysis, thus advancing our understanding of spinal health.

PMID:37892966 | DOI:10.3390/bioengineering10101236

The London Spine Unit : top spinal hospital in UK

Read the original publication:

Machine Learning-Based Measurement of Regional and Global Spinal Parameters Using the Concept of Incidence Angle of Inflection Points

Related Posts

0/5 (0 Reviews)

Trusindex Reviews

London Spine Unit Harley Street Hospital

A Focus on High Quality Specialised Care

We are a specialist Private Hospital based on Harley Street, London UK The Harley Street Hospital, Day Surgery Hospital

We provide exclusive health services for individuals seeking Advanced medical, non-surgical or minimally invasive treatments. We are covered by All Insurance Companies apart from AXA PPP

Our Medical Director and Lead Spinal Surgeon Mr Mo Akmal MD is a world renowned Spine Specialist Consultant with over 20 years of experience. He and his team have developed revolutionary techniques to perform all types of Spinal Surgery as a Day Case procedure without traditional General Anaesthetic.

We are constantly improving our techniques for treatment and improving facilities for our patients.

Book your Appointment Now 
Check out our Reviews 
Check out our Patient Videos 
Check our Mr Akmal’s Profile

 

What our patients say ...

Bioengineering (Basel). 2023 Oct 23;10(10):1236. doi: 10.3390/bioengineering10101236.ABSTRACTThis study delves into the application of convolutional neural networks (CNNs) in evaluating spinal sagittal alignment, introducing the innovative concept of incidence angles of inflection points (IAIPs) as intuitive parameters to capture the interplay between pelvic and spinal alignment. Pioneering the fusion of IAIPs with machine learning for sagittal

Revolutionary Keyhole surgical technique to vaporise bulging discs

Dr Mo Akmal Medical Director
Dr Mo Akmal MD - Lead Spinal Surgeon

Laser Disc Surgery can be performed under local anaesthetic at The Harley Street Hospital.

Initial Consultation

with Consultant Spine Surgeon
£ 250
  • No Waiting Times
  • Top NHS affiliated Consultant
  • Includes Clinical Review and Report
  • Multidisciplinary discussion
  • Review of Previous Scans and Reports

Follow up Consultation

any appointment after initial consultation
£ 180
  • Top NHS affiliated Consultant
  • Includes Clinical Review and Report
  • Multidisciplinary discussion

High Resolution MRI Scan

any Single Region (3.0 Tesla)
£ 600
  • No waiting times
  • Includes Full Radiologist Report
  • Open or Closed MRI scan types
  • Copy of Scan on CD

Website Offer

Pre-Booked Online
£1130
£ 800
  • Initial Consultation
  • MRI Scan (Single Region)
  • Follow Up consultation
  • Same Day One Stop Visit
  • Full Medical and MRI scan Report
  • Copy of scan on CD
Popular

If you have any emergency Doctor’s need, simply call our 24 hour emergency

Your personal case manager will ensure that you receive the best possible care.

Call Now 

+44 844 589 2020
+44 203 973 8810