# PlaTiF: A pioneering dataset for orthopedic insights in AI-powered diagnosis of tibial plateau fractures

## TL;DR

PlaTiF is a new open-access dataset of knee X-rays for training AI to diagnose and classify tibial plateau fractures more accurately and efficiently.

## Contribution

The paper introduces the first open-access dataset for AI-based analysis of tibial plateau fractures with expert annotations and bone masks.

## Key findings

- The dataset includes 421 radiographs from 186 patients with fractures classified using the Schatzker system.
- All images are segmented to support AI training and automated fracture assessment.
- The dataset supports applications in fracture detection, classification, and orthopedic education.

## Abstract

Tibial plateau fractures account for approximately 1% of skeletal fractures, with treatment strategies varying based on fracture type, displacement, and articular involvement. Diagnosis is labor-intensive, time-consuming, repetitive, and subject to considerable inter-observer variability. Automated and precise approaches could improve accuracy and efficiency in fracture severity classification. With advances in artificial intelligence (AI), especially deep learning, such techniques are increasingly applied in medicine, yet their performance depends on high-quality training data. Here, we present a first-of-its-kind open-access dataset for AI-based analysis of tibial plateau fractures. The dataset comprises 421 heterogeneous anterior-posterior radiographs from 186 patients (mean age 45.88 ± 17.54 years; 37 females, 149 males), including normal and fractured knees. Fractures were classified by expert orthopedic surgeons and radiologists using the Schatzker system: type I (14.51%), II (18.27%), III (6.45%), IV (5.91%), V (6.45%), VI (17.20%), and normal (31.18%). All images were segmented to generate tibial bone masks, supporting morphological analysis, AI training, and automated fracture assessment. This dataset facilitates AI-driven fracture detection, classification, preoperative planning, and orthopedic assistant education.