Radiographic Analysis of Scoliosis using Convolutional Neural Network in Clinical Practice-Reference-Cited by-同舟云学术

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Radiographic Analysis of Scoliosis using Convolutional Neural Network in Clinical Practice

Published:2024 Issue: Volume:85 Page:
ISSN:2951-0805
Container-title:Journal of the Korean Society of Radiology
language:en
Short-container-title:J Korean Soc Radiol

Author:

Oh Ha Yun¹^ORCID,Kim Tae Kun¹²^ORCID,Choi Yun Sun¹^ORCID,Park Mira³^ORCID,Yoon Ra Gyoung¹^ORCID,An Jin Kyung¹^ORCID

Affiliation:

1. Department of Radiology, Nowon Eulji Medical Center, Eulji University, Seoul, Korea.

2. Department of Radiology, Armed Forces Seoul District Hospital, Seoul, Korea.

3. Department of Preventive Medicine, School of Medicine, Eulji University, Daejeon, Korea.

Publisher

XMLink

Link

https://jksronline.org/pdf/10.3348/jksr.2023.0111

Reference18 articles.

1. Scoliosis Imaging: What Radiologists Should Know

2. Radiographic Evaluation of Scoliosis:Review

3. Automating Scoliosis Measurements in Radiographic Studies with Machine Learning: Comparing Artificial Intelligence and Clinical Reports

4. Measurement of scoliosis and kyphosis radiographs. Intraobserver and interobserver variation.

5. Reliability analysis for manual measurement of coronal plane deformity in adolescent scoliosis. Are 30 × 90 cm plain films better than digitized small films?

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