An image processing algorithm to estimate bone mineral density using digital X-ray images
01 Feb 2017-pp 1-4
TL;DR: An image processing algorithm that estimates the bone mineral density from digital X-ray images itself can reduce cost; reduce the time for detecting the patient status and also it is a non-invasive method.
Abstract: The main idea of this paper is to test and validate an image processing algorithm that estimates the bone mineral density from digital X-ray (both real-time and open source) images itself. This method can reduce cost; reduce the time for detecting the patient status and also it is a non-invasive method.
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TL;DR: 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.
Abstract: 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, a...
5 citations
TL;DR: In this article , a computer-aided diagnostic system capable of detecting osteoporosis more effectively using digital X-ray images was proposed, which consists of two stages: pre-processing and post-processing.
Abstract: AbstractBones are the most significant anatomical moving parts in humans. Osteoporosis is a bone disease that is a serious global public health problem. It is one of the most severe diseases that may be diagnosed sooner using medical imaging techniques. The bone mineral density (BMD) test is the gold standard for diagnosing osteoporosis. The goal of this research is to establish a computer-aided diagnostic system capable of detecting osteoporosis more effectively using digital X-ray images. The methodology in this paper consists of two stages: pre-processing and post-processing. In pre-processing, the digital X-ray images are rescaled and denoised to improve their quality. These images are then used to estimate BMD scores, which, in turns, are utilized to identify the patient’s condition. A comparison with existing methods confirms that the proposed approach is fairly promising for detecting osteoporosis conditions.KeywordsBone mineral densityOsteoporosisOsteopeniaX-ray imageMATLAB
01 Jan 2021
TL;DR: In this article, the authors reviewed different medical imaging techniques like X-Ray, DEXA, SR µCT, Photo Acoustic Imaging, Quantitative Ultrasound to do bone mineral density analysis and concluded that Dual Energy X-ray Absorptiometry (DEXA) will be a more useful diagnostic modality for rapid investigation of bone health.
Abstract: The healthiness of bone is decided by organic as well as inorganic contents. Inappropriate proportions of organic (collagen) and inorganic (minerals) contents give rise to fractures and diseases like arthritis, osteopenia, and osteoporosis. Bone Mineral Density (BMD) is a commonly used inorganic clinical indicator to determine the quality of bone. There are invasive methods like chemical quantitative analysis, and noninvasive methods include imaging techniques, to find the composition of bone. This paper is to review different medical imaging techniques like X-Ray, DEXA, SR µCT, Photo Acoustic Imaging, Quantitative Ultrasound to do bone mineral density analysis. The study concludes that the imaging technique Dual Energy X-ray Absorptiometry (DEXA) will be a more useful diagnostic modality for rapid investigation of bone health. It is a two-dimensional imaging tool that calculates a ratio of Bone Mineral Contents (BMC) with an area of bone is known as areal BMD. But the shortcoming of DEXA technique is that the bones of different lengths may produce the same BMD results by maintaining the equal ratio thereby indicating incorrect strength of bones. Hence along with the area, we have to take into account the thickness of the bone to predict BMD.
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Book•
01 Jan 1997
TL;DR: This text includes discussions about the development of models to predict how bone will adapt to changes in the mechanical loading situation, and the morphology of trabecular bone structure.
Abstract: This text focuses on the structure of bone and how that affects its mechanical behaviour. It includes discussions about the development of models to predict how bone will adapt to changes in the mechanical loading situation, and the morphology of trabecular bone structure.
44 citations
01 Jan 2007
TL;DR: In this paper, texture analysis techniques were used to characterize the trabecular pattern changes in proximal femur recorded in radiographs that lead to osteoporosis detection.
Abstract: The most common approach to the study of the structural changes with age in the proximal femur is by means of the Singh index However, subjectivity of its grades determination may limit its practical value In this paper, we used several texture analysis techniques to characterize the trabecular pattern changes in proximal femur recorded in radiographs that lead to osteoporosis detection Texture analysis was used to rank 41 radiographs and then compared to Singh index grading performed by experienced experts We compare three texture analysis methods namely Gabor filter, wavelet transforms and fractal dimension to extract the features that represent the structural change in trabecular pattern The assessment of osteoporosis can be performed by observing and analyzing the trabecular patterns recorded in proximal femur radiographs The predetermined Singh indexes of trabecular pattern are used to justify the classification result The features extracted using Gabor filter, wavelet transform and fractal analysis are found to be significantly correlated with predetermined Singh indexes (r=087, r=084 and r=079 with p=0001)
36 citations