| Abstrakt: |
Osteoporosis is one of the common bone diseases that reduces bone strength and affects the structure of the bone and thereby increases the chances of fracture risk, more likely in the spine, hip, and wrist. The diagnosis of osteoporosis is done by measuring the bone quality and bone mass, mainly bone mineral density (BMD). There are various methods available to measure the BMD. Of which, Dual Energy X-ray Absorptiometry (DEXA) is considered as the benchmark method. BMD is a parameter to determine the important score known as T-score that determines the osteoporosis condition. BMD measurement is visualized in X-ray images and DEXA images. This survey article focuses on the measurement of BMD using various benchmark image processing algorithms such as image enhancement, segmentation, and texture analysis on X-ray and DEXA images for osteoporosis detection. Superior properties of DEXA uncover the prospective for new medical applications and researches. The article reviews the early methods of BMD measurements in a nutshell. Also, the article mainly explains the features that are on par with the X-ray and DEXA images. The article explains the image processing algorithms used for osteoporosis detection. The methods such as pre-processing, feature extraction, and segmentation methods are explained for both X-ray and DEXA imaging modalities. |
