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

Global Context Modeling in YOLOv8 for Pediatric Wrist Fracture Detection

This repository contains the official code for the paper "Enhancing wrist abnormality detection with YOLO: Analysis of state-of-the-art single-stage detection models". We achieved SOTA fracture detection results on GRAZPEDWRI-DX dataset. Also contains code for end-to-end application.

Detection of cracks in the building foundation

This repository contains the official code for the paper "Learning from the Few: Fine-grained Approach to Wrist Pathology Recognition on a Limited Dataset".

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.

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 the official code for the paper "Pediatric Wrist Fracture Detection in X-rays via YOLOv10 Algorithm and Dual Label Assignment System"

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.

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 yolov10, with that custom dataset, to indicate fractures in x-rays. The project uses 5 cascade models, if one does not detect fracture it is passed to another

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

Using deep learning to classify wrist fractures from GRAZPEDWRI-DX dataset. Pinpointing important regions using the XAI algorithm GradCAM.

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