Enhanced Detection Performance of Acute Vertebral Compression Fractures Using a Hybrid Deep Learning and Traditional Quantitative Measurement Approach: Beyond the Limitations of Genant Classification

Enhanced Detection Performance of Acute Vertebral Compression Fractures Using a Hybrid Deep Learning and Traditional Quantitative Measurement Approach: Beyond the Limitations of Genant Classification

Objective: This study evaluated the applicability of the classical method, height loss ratio (HLR), for identifying major acute compression fractures in clinical practice and compared its performance with deep learning (DL)-based VCF detection methods. Additionally, it examined whether combining the...

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Bibliographic Details
Main Authors: Jemyoung Lee, Minbeom Kim, Heejun Park, Zepa Yang, Ok Hee Woo, Woo Young Kang, Jong Hyo Kim
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Bioengineering
Subjects:
acute vertebral compression fracture
genant classification
deep learning
computed tomography
spine
Online Access:https://www.mdpi.com/2306-5354/12/1/64
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