Automated Risser Grade Assessment of Pelvic Bones Using Deep Learning
(1) Background: This study aimed to develop a deep learning model using a convolutional neural network (CNN) to automate Risser grade assessment from pelvic radiographs. (2) Methods: We used 1619 pelvic radiographs from patients aged 12–18 years with scoliosis to train two CNN models—one for the rig...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-05-01
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| Series: | Bioengineering |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2306-5354/12/6/589 |
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