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Jeon YD, Kang MJ, Kuh SU, Cha HY, Kim MS, You JY, Kim HJ, Shin SH, Chung YG, Yoon DK. Deep Learning Model Based on You Only Look Once Algorithm for Detection and Visualization of Fracture Areas in Three-Dimensional Skeletal Images. Diagnostics (Basel) 2023; 14:11. [PMID: 38201320 PMCID: PMC10802847 DOI: 10.3390/diagnostics14010011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 11/30/2023] [Accepted: 12/10/2023] [Indexed: 01/12/2024] Open
Abstract
Utilizing "You only look once" (YOLO) v4 AI offers valuable support in fracture detection and diagnostic decision-making. The purpose of this study was to help doctors to detect and diagnose fractures more accurately and intuitively, with fewer errors. The data accepted into the backbone are diversified through CSPDarkNet-53. Feature maps are extracted using Spatial Pyramid Pooling and a Path Aggregation Network in the neck part. The head part aggregates and generates the final output. All bounding boxes by the YOLO v4 are mapped onto the 3D reconstructed bone images after being resized to match the same region as shown in the 2D CT images. The YOLO v4-based AI model was evaluated through precision-recall (PR) curves and the intersection over union (IoU). Our proposed system facilitated an intuitive display of the fractured area through a distinctive red mask overlaid on the 3D reconstructed bone images. The high average precision values (>0.60) were reported as 0.71 and 0.81 from the PR curves of the tibia and elbow, respectively. The IoU values were calculated as 0.6327 (tibia) and 0.6638 (elbow). When utilized by orthopedic surgeons in real clinical scenarios, this AI-powered 3D diagnosis support system could enable a quick and accurate trauma diagnosis.
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Affiliation(s)
- Young-Dae Jeon
- Department of Orthopedic Surgery, University of Ulsan College of Medicine, Ulsan University Hospital, Ulsan 44033, Republic of Korea
| | - Min-Jun Kang
- Department of Integrative Medicine, College of Medicine, Yonsei University of Korea, Seoul 03722, Republic of Korea;
| | - Sung-Uk Kuh
- Department of Integrative Medicine, College of Medicine, Yonsei University of Korea, Seoul 03722, Republic of Korea;
| | - Ha-Yeong Cha
- Industrial R&D Center, KAVILAB Co., Ltd., Seoul 06675, Republic of Korea; (H.-Y.C.); (M.-S.K.); (J.-Y.Y.); (H.-J.K.)
| | - Moo-Sub Kim
- Industrial R&D Center, KAVILAB Co., Ltd., Seoul 06675, Republic of Korea; (H.-Y.C.); (M.-S.K.); (J.-Y.Y.); (H.-J.K.)
| | - Ju-Yeon You
- Industrial R&D Center, KAVILAB Co., Ltd., Seoul 06675, Republic of Korea; (H.-Y.C.); (M.-S.K.); (J.-Y.Y.); (H.-J.K.)
| | - Hyeon-Joo Kim
- Industrial R&D Center, KAVILAB Co., Ltd., Seoul 06675, Republic of Korea; (H.-Y.C.); (M.-S.K.); (J.-Y.Y.); (H.-J.K.)
| | - Seung-Han Shin
- Department of Orthopedic Surgery, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea; (S.-H.S.); (Y.-G.C.)
| | - Yang-Guk Chung
- Department of Orthopedic Surgery, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea; (S.-H.S.); (Y.-G.C.)
| | - Do-Kun Yoon
- Industrial R&D Center, KAVILAB Co., Ltd., Seoul 06675, Republic of Korea; (H.-Y.C.); (M.-S.K.); (J.-Y.Y.); (H.-J.K.)
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