OrthoFrac-XR: Clinically Validated X-ray Images for Bone Fracture Detection

1,493 fully classified orthopedic X-ray images from approximately 1,300 distinct patients, collected from several Bangladeshi institutions. The dataset was created by Md. Arham Tabib and last updated on April 28, 2026. It includes a structured metadata file with clinical data such as patient age, gender, bone type, and fracture measurements.

Use Cases

• Training fracture detection models based on high-resolution X-ray images.
• Classifying fracture types (distal, proximal, post-fracture) based on the four clinically significant classes.
• Conducting integrated radiographic-clinical analysis based on the structured metadata containing patient demographics and fracture measurements.
• Developing models for resource-limited healthcare settings based on the dataset's focus on accessible X-ray imaging.

Strengths

• 1,493 images independently validated by orthopedic specialists from Dhaka Medical College for labeling reliability.
• Includes a structured metadata file (bone_metadata.csv) with clinically significant data like fracture gap measurements and primary clinical observations.
• Images are divided into four clinically significant classes: distal fracture (314 images), proximal fracture (254 images), post-fracture (349 images), and non-fracture (576 images).

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count for the metadata file is unknown, which may limit suitability assessment.
• Data reflects a geographic bias, having been collected solely from Bangladeshi institutions.

Provenance

Source

Several Bangladeshi institutions.

Collection Method

Collected and independently validated by orthopedic specialists.

Time Range

null

Freshness

Last updated 2026-04-28 04:19:12; freshness should be verified.

Geography

Bangladesh