mlsanityData to 7 Oct 2026

YOLOv9 for Fracture Detection in Pediatric Wrist Trauma X-ray Images

arXiv 2403.11249 ↗First posted 17 Mar 2024eess.IV cs.CVcited by 10

Not on the map. Why?

Abstract (arXiv)

The introduction of YOLOv9, the latest version of the You Only Look Once (YOLO) series, has led to its widespread adoption across various scenarios. This paper is the first to apply the YOLOv9 algorithm model to the fracture detection task as computer-assisted diagnosis (CAD) to help radiologists and surgeons to interpret X-ray images. Specifically, this paper trained the model on the GRAZPEDWRI-DX dataset and extended the training set using data augmentation techniques to improve the model performance. Experimental results demonstrate that compared to the mAP 50-95 of the current state-of-the-art (SOTA) model, the YOLOv9 model increased the value from 42.16% to 43.73%, with an improvement of 3.7%. The implementation code is publicly available at https://github.com/RuiyangJu/YOLOv9-Fracture-Detection.

Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). Builds on 21 of its 47 references that are in the map. First posted on arXiv 17 Mar 2024.

Builds on

21 of 47 references.

References · 21

  1. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  2. 2014Microsoft COCO: Common Objects in Contextcited by 17,498
  3. 2015You Only Look Once: Unified, Real-Time Object Detectioncited by 4,829
  4. 2017Squeeze-and-Excitation Networkscited by 4,763
  5. 2018CBAM: Convolutional Block Attention Modulecited by 2,463
  6. 2020YOLOv4: Optimal Speed and Accuracy of Object Detectioncited by 1,624
  7. 2021YOLOX: Exceeding YOLO Series in 2021cited by 1,064
  8. 2016An overview of gradient descent optimization algorithmscited by 1,021
  9. 2022YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectorscited by 978
  10. 2019ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networkscited by 572
  11. 2024YOLOv9: Learning What You Want to Learn Using Programmable Gradient Informationcited by 422
  12. 2019CSPNet: A New Backbone that can Enhance Learning Capability of CNNcited by 381
9 more
  1. 2022YOLOv6: A Single-Stage Object Detection Framework for Industrial Applicationscited by 273
  2. 2021You Only Learn One Representation: Unified Network for Multiple Taskscited by 86
  3. 2021SA-Net: Shuffle Attention for Deep Convolutional Neural Networkscited by 54
  4. 2021Global Attention Mechanism: Retain Information to Enhance Channel-Spatial Interactionscited by 39
  5. 2022Designing Network Design Strategies Through Gradient Path Analysiscited by 32
  6. 2023Fracture Detection in Pediatric Wrist Trauma X-ray Images Using YOLOv8 Algorithmcited by 12
  7. 2023Resolution Enhancement Processing on Low Quality Images Using Swin Transformer Based on Interval Dense Connection Strategycited by 9
  8. 2024YOLOv8-AM: YOLOv8 Based on Effective Attention Mechanisms for Pediatric Wrist Fracture Detectioncited by 7
  9. 2018Detection of distal radius fractures trained by a small set of X-ray images and Faster R-CNNcited by 6

Built on by

Cited by year

Citing papers per year: 2024: 7; 2025: 3.

10 papers.