BEAUT: a radiomic approach to identify potential lumbar fractures in magnetic resonance imaging
Author:
Funder
São Paulo Research Foundation – FAPESP
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9474585/9474649/09474751.pdf?arnumber=9474751
Cited by 4 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. Fast and accurate 3-D spine MRI segmentation using FastCleverSeg;Magnetic Resonance Imaging;2024-06
2. Machine learning model based on radiomics features for AO/OTA classification of pelvic fractures on pelvic radiographs;PLOS ONE;2024-05-30
3. Analysis of vertebrae without fracture on spine MRI to assess bone fragility: A Comparison of Traditional Machine Learning and Deep Learning;2022 IEEE 35th International Symposium on Computer-Based Medical Systems (CBMS);2022-07
4. Wia-Spine: A CBIR environment with embedded radiomic features to assess fragility fractures;2022 IEEE 35th International Symposium on Computer-Based Medical Systems (CBMS);2022-07
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