Recently, automatic disease diagnosis based on medical images has become an integral part of digital pathology packages. To create, develop, evaluate, and compare these systems, we need diverse data sets. One of the key features in the diagnosis of bone diseases is measuring bone mineral density (BMD). Most research in this field uses manual methods to directly extract bone image features despite the underlying correlation between diseased and healthy bones, which explains the limited results. Detection of significant changes in bone mineral density (BMD) relies on minimally invasive dual energy x-ray absorptiometry (DXA) scanners. This article presents a collection of bone density test results along with a patient profile called Arak Bone Densitometry Center data. The patient profile includes height and weight and information about the patient, along with photos of the imaging areas. The number of these patients is 3,643, with about 4,020 photos stored next to them. Which can be used to develop automatic disease diagnosis methods and software.

Dataset https://drive.google.com/drive/folders/1HmLTG4GFgB2s4D0×7TTRx8vV_VWY3sW3?usp=sharing

The authors have declared no competing interest.

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The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

Central to this ethical framework was the rigorous scrutiny and approval process facilitated by the ethics committee of the Arak Bone Density Measurement Center

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