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HBFMID, the full name of which is Human Bone Fractures Multi-modal Image Dataset, is a medical imaging dataset released by the American International University, Bangladesh in 2024. It aims to provide support for fracture detection and classification tasks.

The dataset contains X-rays and MRI images of the elbow, fingers, forearm, humerus, shoulder, femur, tibia, knee, hip, wrist, spine, and some healthy bones. The dataset initially collected 641 original images (510 X-rays and 131 MRI images) and divided them into a training set of 449, a validation set of 128, and a test set of 64. All images were automatically oriented, resized (640×640), and contrast enhanced. Based on the training set, enhancement methods such as flipping, rotation, scaling, shearing, and brightness and saturation changes were further applied to generate approximately 1,347 augmented samples. The final dataset contains 1,539 images.

This dataset integrates multimodal images, covers multiple parts, and has various display forms. It is fully enhanced and clearly divided. It is suitable for training and evaluating fracture detection and classification models, and is especially valuable in medical image analysis and deep learning research.