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Hybrid Area-based Techniques for Muscle Mass Identification on Dual Energy X-Ray Absorptiometry Images

In clinical routine, a number of radiation techniques are used to diagnose physical health conditions. The most common are CT-Scan and X-Ray techniques. Each of the techniques has its pros and cons. For example, CT-Scan is often used to gain a very clear composition of the organs under inspection. However, a person may suffer from a large volume of radiation exposure. Dual Energy X-ray Absorptiometry - DXA is often an alternative to CT-Scan. This is due to the fact that the DXA technique diffuses low doses of radiation. As a result, an image generated with a DXA technique often has less information than those generated by a CT-Scan technique. However, DXA's role in sarcopenia diagnosis is emerging. In this respect, the detection of muscle mass changes in sarcopenia diagnosis requires follow up treatment. Thus, there is a need for a method to improve the DXA produced images that can be used to help identify the muscle area more accurately. This paper proposes an approach to enhance the original DXA image to make it more appropriate to support an expert's diagnosis. The accuracy results measured with JI, CM, DS, and HD demonstrates that the proposed method outperformed other methods with the results on each class as follows: Class A: 0.68, 0.75, 0.81, and 17.61 respectively; Class B: 0.62, 0.64, 0.76, and 16.99 respectively; Class C: 0.52, 0.48, 0.68, and 18.75 respectively.