YOLOv8-AM: YOLOv8 with Attention Mechanisms for Pediatric Wrist Fracture Detection

Fracture Detection in Pediatric Wrist Trauma X-ray Images Using YOLOv8 Algorithm

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

Detection of cracks in the building foundation

This study employs state-of-the-art YOLO models. We achieved SOTA fracture detection results on GRAZPEDWRI-DX dataset. Paper Link: https://www.sciencedirect.com/science/article/pii/S1746809424002027

Global Context Modeling in YOLOv8 for Pediatric Wrist Fracture Detection

Indicates the location of wrist fractures in x-rays through training with yolo v8 of roboflow images downloaded from https://www.kaggle.com/datasets/pkdarabi/bone-fracture-detection-computer-vision-project/code

This repository contains code of YOLOv10 for Automated Fracture Detection in Pediatric Wrist Trauma X-rays.

From a selection of data from the Roboflow file https://universe.roboflow.com/landy-aw2jb/fracture-ov5p1/dataset/1, which represents a reduced but homogeneous version of that file, a model is obtained based on yolov10 with that custom dataset to indicate fractures in x-rays.

From dataset https://universe.roboflow.com/roboflow-100/bone-fracture-7fylg a model is obtained, based on yolov10, with that custom dataset, to indicate fractures in x-rays.

From a selection of data from the Roboflow file https://universe.roboflow.com/landy-aw2jb/fracture-ov5p1/dataset/1, which represents a reduced but homogeneous version of that file, a model is obtained using an adaptation of the project https://www.kaggle.com/code/nyachhyonjinu/yolov3-test instead any yolo model

Detection of fractures in radiographs by obtaining the X and Y coordinates of the center of the fracture applying ML (SVR) to obtain the values ​​of these coordinates separately. It is applied to a selection of data from the Roboflow file https://universe.roboflow.com/landy-aw2jb/fracture-ov5p1/dataset/1

This project uses PyTorch to classify bone fractures. As well as fine-tuning some famous CNN architectures (like VGG 19, MobileNetV3, RegNet,...), we designed our own architecture. Additionally, we used Transformer architectures (such as Vision Transformer and Swin Transformer). This dataset is Bone Fracture Multi-Region X-ray, available on Kaggle.

From dataset https://universe.roboflow.com/roboflow-100/bone-fracture-7fylg a model is obtained, based on ML (SVR), with that custom dataset, to indicate fractures in x-rays.