Automated femur segmentation from computed tomography images using a deep neural network-Reference-Cited by-同舟云学术

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Automated femur segmentation from computed tomography images using a deep neural network

Published:2021-02-15 Issue: Volume: Page:
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Container-title:Medical Imaging 2021: Biomedical Applications in Molecular, Structural, and Functional Imaging
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Author:

Bjornsson Pall A.,Helgason Benedikt,Palsson Halldor,Sigurdsson Sigurdur,Gudnason Vilmundur,Ellingsen Lotta M.

Publisher

SPIE

Cited by 7 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Better Rough Than Scarce: Proximal Femur Fracture Segmentation With Rough Annotations;IEEE Transactions on Medical Imaging;2024-09

2. Subtracting–adding strategy for necrotic lesion segmentation in osteonecrosis of the femoral head;International Journal of Computer Assisted Radiology and Surgery;2024-03-02

3. SSDL—an automated semi-supervised deep learning approach for patient-specific 3D reconstruction of proximal femur from QCT images;Medical & Biological Engineering & Computing;2024-01-13

4. A CNN-based strategy to automate contour detection of the hip and proximal femur using DXA hip images from longitudinal databases (CLSA and CaMos);Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization;2023-12-26

5. Semi-Supervised Learning Based Femur Segmentation from QCT Images;2023 International Conference on Machine Learning and Applications (ICMLA);2023-12-15

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