Pediatric Wrist Fracture Detection Using Feature Context Excitation Modules in X‐ray Images
學年 114
學期 1
出版（發表）日期 2025-12-26
作品名稱 Pediatric Wrist Fracture Detection Using Feature Context Excitation Modules in X‐ray Images
作品名稱（其他語言）
著者 Rui‐Yang Ju; Chun‐Tse Chien; Enkaer Xieerke; Jen‐Shiun Chiang
單位
出版者
著錄名稱、卷期、頁數 IET Image Processing 20(1), e70269
摘要 Children often suffer wrist trauma in daily life and typically require radiologists to analyse and interpret X-ray images before undergoing surgical treatment. The development of deep learning has enabled neural networks to serve as computer-aided diagnosis (CAD) tools, assisting doctors and experts in medical image diagnostics. Since the you only look once version-8 (YOLOv8) model has achieved satisfactory success in object detection tasks, it has been applied to various fracture detection tasks. This work introduces four variants of feature contexts excitation-YOLOv8 (FCE-YOLOv8) model, each incorporating a different FCE module (i.e., modules of squeeze-and-excitation (SE), global context (GC), gather-excite (GE), and Gaussian context transformer (GCT)) to enhance the model performance. Experimental results on the GRAZPEDWRI-DX dataset demonstrate that our proposed YOLOv8 + GC-M3 model improves the mAP val 50 value from 65.78% to 66.32%, outperforming the state-of-the-art (SOTA) model while reducing inference time. Furthermore, our proposed YOLOv8 + SE-M3 model achieves the highest mAP val 50 value of 67.07%, exceed- ing the SOTA performance. The implementation of this work is publicly available at https://github.com/RuiyangJu/FCE-YOLOv8 .
關鍵字 computer vision; feature contexts excitation; fracture detection; medical image diagnostics; medical image processing; object detection; you only look once (YOLO)
語言 en
ISSN 1751-9667; 1751-9659
期刊性質 國外
收錄於 SCI
產學合作
通訊作者
審稿制度 否
國別 GBR
公開徵稿
出版型式 ,電子版,紙本
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