ICONIP 2024 (IEEE Access 2025)

Scientific Reports 2023

Electronics Letters 2024

Lightweight G-YOLOv11: Advancing Efficient Fracture Detection in Pediatric Wrist X-rays

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.

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"

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.

ISPACS 2024

Detection of cracks in the building foundation

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

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

This repository contains the implementation code of the paper "Small Data, Big Impact: A Multi-Locale Bone Fracture Detection on an Extremely Limited Dataset Via Crack-Informed YOLOv9 Variants"

Deep learning-based model for automated classification of cervical spine fractures with a remarkable 99.67% accuracy, surpassing radiologists' performance. Utilizes AlexNet and GoogleNet architectures for efficient and fast diagnosis in medical applications, enhancing clinical and research-based workflows.

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

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.

# Fracture.v1i_Reduced_SSD 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, try to perform fracture detection using SSD. A version with VGG16 and another with only linear layers are presented

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.

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://github.com/mahdi-darvish/YOLOv3-from-Scratch-Analaysis-and-Implementation instead any yolo model

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

Fracture Detection in Arm X-rays using YOLOv8 — A deep learning web application built with Python, Flask, OpenCV, and YOLOv8 to automatically detect and highlight fractures in arm X-ray images using real-time object detection.