"Structure-Aware Sparse-View X-ray 3D Reconstruction" (CVPR 2024) - A Toolbox for CT reconstruction and X-ray Novel View Synthesis

"Radiative Gaussian Splatting for Efficient X-ray Novel View Synthesis" (ECCV 2024)

"Rectifying Radiative Gaussian Splatting for Tomographic Reconstruction" (NeurIPS 2024)

The aim of this study is automatic semantic segmentation in one-shot panoramic x-ray image by using deep learning method with U-Net Model and binary image analysis in order to provide diagnostic information for the management of dental disorders, diseases, and conditions.

List of datasets and papers in X-ray security images (Computer vision/Machine Learning)

X-ray Images (Chest images) analysis and anomaly detection using Transfer learning with inception v2

12000+ manually drawn pixel-level lung segmentations, with and without covid

Use Deep Learning model to diagnose 14 pathologies on Chest X-Ray and use GradCAM Model Interpretation Method

Knee Osteoarthritis Analysis with X-ray Images using CNN

A Flask Pneumonia Detection web app from chest X-Ray Images using CNN

Lung Segmentations of COVID-19 Chest X-ray Dataset.

This is our working repository for the project - spine curvature estimation. It contains all the implementation codes and results of our approach.

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Official Python implementation for XVis Toolbox release with the book Computer Vision for X-Ray Testing.

Web app to predict knee osteoarthritis grade using Deep Learning and Streamlit

Python implementation for Balu, a computer vision, pattern recognition and image processing library. Originally implemented in matlab by Domingo Mery.

本项目实现了一个基于深度学习的胸部X线图像肺炎分类系统，用于自动识别儿科患者的胸部X线图像中是否存在肺炎（正常/肺炎）。系统采用了多种先进的深度学习模型，包括ResNet50、EfficientNet、Vision Transformer (ViT)和Swin Transformer，并支持模型集成。

Complete U-net Implementation with keras

[ACCV 2024 (Oral)] Official Implementation of "RayEmb: Arbitrary Landmark Detection in X-Ray Images Using Ray Embedding Subspace", Pragyan Shrestha, Chun Xie, Yuichi Yoshii, Itaru Kitahara

Lung Bounding Boxes of COVID-19 Chest X-ray Dataset.

an X-ray image dataset for prohibited item segmentation

Code for StyleGAN-based simulation of X-ray baggage images for security screening

Bruker's TOPAS X-ray diffraction calculations parser

Analysis of Abnormality in Humerus X-Ray images using DenseNet

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.

In this notebook, we perform a binary classification on chest X-ray images to determine whether a person has healthy lungs or is diagnosed with pneumonia. For this classification, we used a custom deep convolutional neural network (CNN) model and achieved an accuracy of 95% on the test set.

Using deep learning a U-net architecture is used to make segmentation, detection, and extraction of the lower left third molar. The result of the proposed U-net is compared with Attention U-net and U-net++.

GPT-2 based medical reports generator for X-ray images in Czech.

Award-winning covid x-ray detection, with over 90% SP PP PN SN and 99% training and validation accuracies.

Use EuXFEL detector geometry to assemble images