Multimodal radiomics and deep learning models for predicting early femoral head deformity in LCPD.

Journal: European journal of radiology

Published Date: Oct 19, 2024

Abstract

PURPOSE: To develop a predictive model combining clinical, radiomic, and deep learning features based on X-ray and MRI to identify risk factors for early femoral head deformity in Legg-Calvé-Perthes disease (LCPD).

Authors

Dian Zhang

School of Computer Science, Northwestern Polytechnical University, Xi'An, 710129, ShaanXi, China. Electronic address: dianzhang@mail.nwpu.edu.cn.
Ya-Nan Li

Department of Radiology, Xuzhou Children's Hospital, Xuzhou, China.
Cheng-Long Li

Department of Radiology, Xuzhou Children's Hospital, Xuzhou, China. Electronic address: lcllmm@163.com.
Wan-Liang Guo

Department of Radiology, Children's Hospital of Soochow University, Suzhou 215025, China.

Keywords

Child Child, Preschool Deep Learning Female Femur Head Humans Legg-Calve-Perthes Disease Magnetic Resonance Imaging Male Multimodal Imaging Predictive Value of Tests Radiomics Retrospective Studies

External Resources

View on PubMed Access via DOI PubMed (39454426)

Multimodal radiomics and deep learning models for predicting early femoral head deformity in LCPD.

Abstract

Authors

Keywords

External Resources

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