A Two-Stage Deep Learning Method for Auxiliary Diagnosis of Upper Limb Fractures Based on ResNet-50 and Enhanced YOLO
Aiming at the problem that the existing auxiliary diagnosis methods for fractures are mostly limited to specific body parts and lack generality and robustness when applied to multi-part diagnoses, this study proposes a two-stage upper limb fracture auxiliary diagnosis method based on deep learning a...
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MDPI AG
2025-06-01
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| Series: | Mathematics |
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| author | Hongxiao Wang Zhe Li Dingsen Zhang |
| author_facet | Hongxiao Wang Zhe Li Dingsen Zhang |
| author_sort | Hongxiao Wang |
| collection | DOAJ |
| description | Aiming at the problem that the existing auxiliary diagnosis methods for fractures are mostly limited to specific body parts and lack generality and robustness when applied to multi-part diagnoses, this study proposes a two-stage upper limb fracture auxiliary diagnosis method based on deep learning and develops a corresponding auxiliary diagnosis system. In the first stage, this study employs an improved ResNet-50 model combined with transfer learning and a Squeeze-and-Excitation (SE) attention mechanism for fracture image localization. In the second stage, an improved You Only Look Once (YOLO) model based on Scale Sequence Feature Fusion (SSFF) and Triple Feature Encoder (TFE) modules is used for fracture diagnoses in different body parts. Contrary to the traditional methods that are tailored to specific body parts, the integrated design approach presented in this paper is better suited to meeting the diagnostic needs of multiple body parts, demonstrating better generality and clinical application potential. |
| format | Article |
| id | doaj-art-01ab38e1a1a54e3f8eea23a20398a641 |
| institution | Kabale University |
| issn | 2227-7390 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj-art-01ab38e1a1a54e3f8eea23a20398a6412025-08-20T03:46:49ZengMDPI AGMathematics2227-73902025-06-011311185810.3390/math13111858A Two-Stage Deep Learning Method for Auxiliary Diagnosis of Upper Limb Fractures Based on ResNet-50 and Enhanced YOLOHongxiao Wang0Zhe Li1Dingsen Zhang2College of Information Science and Engineering, Northeastern University, Shenyang 110819, ChinaCollege of Information Science and Engineering, Northeastern University, Shenyang 110819, ChinaCollege of Information Science and Engineering, Northeastern University, Shenyang 110819, ChinaAiming at the problem that the existing auxiliary diagnosis methods for fractures are mostly limited to specific body parts and lack generality and robustness when applied to multi-part diagnoses, this study proposes a two-stage upper limb fracture auxiliary diagnosis method based on deep learning and develops a corresponding auxiliary diagnosis system. In the first stage, this study employs an improved ResNet-50 model combined with transfer learning and a Squeeze-and-Excitation (SE) attention mechanism for fracture image localization. In the second stage, an improved You Only Look Once (YOLO) model based on Scale Sequence Feature Fusion (SSFF) and Triple Feature Encoder (TFE) modules is used for fracture diagnoses in different body parts. Contrary to the traditional methods that are tailored to specific body parts, the integrated design approach presented in this paper is better suited to meeting the diagnostic needs of multiple body parts, demonstrating better generality and clinical application potential.https://www.mdpi.com/2227-7390/13/11/1858deep learningdiagnostic auxiliary systemfracture imaging |
| spellingShingle | Hongxiao Wang Zhe Li Dingsen Zhang A Two-Stage Deep Learning Method for Auxiliary Diagnosis of Upper Limb Fractures Based on ResNet-50 and Enhanced YOLO Mathematics deep learning diagnostic auxiliary system fracture imaging |
| title | A Two-Stage Deep Learning Method for Auxiliary Diagnosis of Upper Limb Fractures Based on ResNet-50 and Enhanced YOLO |
| title_full | A Two-Stage Deep Learning Method for Auxiliary Diagnosis of Upper Limb Fractures Based on ResNet-50 and Enhanced YOLO |
| title_fullStr | A Two-Stage Deep Learning Method for Auxiliary Diagnosis of Upper Limb Fractures Based on ResNet-50 and Enhanced YOLO |
| title_full_unstemmed | A Two-Stage Deep Learning Method for Auxiliary Diagnosis of Upper Limb Fractures Based on ResNet-50 and Enhanced YOLO |
| title_short | A Two-Stage Deep Learning Method for Auxiliary Diagnosis of Upper Limb Fractures Based on ResNet-50 and Enhanced YOLO |
| title_sort | two stage deep learning method for auxiliary diagnosis of upper limb fractures based on resnet 50 and enhanced yolo |
| topic | deep learning diagnostic auxiliary system fracture imaging |
| url | https://www.mdpi.com/2227-7390/13/11/1858 |
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