Using a convolutional neural network model to derive imaging landmarks for lumbar spine numbering on axial magnetic resonance images-Reference-Cited by-同舟云学术

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Using a convolutional neural network model to derive imaging landmarks for lumbar spine numbering on axial magnetic resonance images

Published:2022-11-16 Issue:2 Volume:33 Page:547-555
ISSN:0899-9457
Container-title:International Journal of Imaging Systems and Technology
language:en
Short-container-title:Int J Imaging Syst Tech

Author:

Yoon Heewon¹^ORCID,Cho Yongwon²^ORCID,Ahn Kyung‐Sik¹^ORCID,Lee Hee‐Gone¹^ORCID,Kang Chang Ho¹^ORCID,Park Beom Jin¹^ORCID

Affiliation:

1. Department of Radiology Korea University Anam Hospital, Korea University College of Medicine Seoul Republic of Korea

2. AI center Korea University Anam Hospital Seoul Republic of Korea

Funder

Korea University Anam Hospital

Publisher

Wiley

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Software,Electronic, Optical and Magnetic Materials

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/ima.22828

Reference23 articles.

1. Using MRI to Evaluate Anatomic Significance of Aortic Bifurcation, Right Renal Artery, and Conus Medullaris When Locating Lumbar Vertebral Segments

2. Numbering of Lumbosacral Transitional Vertebrae on MRI: Role of the Iliolumbar Ligaments

3. Deep Learning in Medical Imaging: General Overview

4. Artificial intelligence and machine learning in spine research

5. Identification of Vertebral Fractures by Convolutional Neural Networks to Predict Nonvertebral and Hip Fractures: A Registry-based Cohort Study of Dual X-ray Absorptiometry

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