Research Output
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PublicationDevelopment of synthetic spine for biomechanical research: An overview( 2021-10-25)Human and animal cadaveric spines are the most common specimens used in biomechanical investigations. However, biological cadaveric spines come with a lot of disadvantages, which resulted in questionable reliability of the data obtained. This motivated the authors to look at the development of a working synthetic spine in motion segments because synthetic materials have been used widely to replace the cadaveric specimens especially for bone testing. The objective of this paper is to provide an overview of the current development of a working synthetic spine and why it is crucial to consider synthetic spine as another alternative specimens to replace human and animal cadaveric spines for biomechanical research. The development of synthetic spines studies in recent years showed a great potential to replicate the human cadaveric spine. Although some of the motions were quite stiff in comparison with human cadaveric motions, with further adjustment, the improved synthetic spine can potentially benefit and transform the spinal biomechanical investigations in the future.
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PublicationSpine Deformity Assessment for Scoliosis Diagnostics Utilizing Image Processing Techniques: A Systematic Review( 2023-10-01)Spinal deformity refers to a range of disorders that are defined by anomalous curvature of the spine and may be classified as scoliosis, hypo/hyperlordosis, or hypo/hyperkyphosis. Among these, scoliosis stands out as the most common type of spinal deformity in human beings, and it can be distinguished by abnormal lateral spine curvature accompanied by axial rotation. Accurate identification of spinal deformity is crucial for a person’s diagnosis, and numerous assessment methods have been developed by researchers. Therefore, the present study aims to systematically review the recent works on spinal deformity assessment for scoliosis diagnosis utilizing image processing techniques. To gather relevant studies, a search strategy was conducted on three electronic databases (Scopus, ScienceDirect, and PubMed) between 2012 and 2022 using specific keywords and focusing on scoliosis cases. A total of 17 papers fully satisfied the established criteria and were extensively evaluated. Despite variations in methodological designs across the studies, all reviewed articles obtained quality ratings higher than satisfactory. Various diagnostic approaches have been employed, including artificial intelligence mechanisms, image processing, and scoliosis diagnosis systems. These approaches have the potential to save time and, more significantly, can reduce the incidence of human error. While all assessment methods have potential in scoliosis diagnosis, they possess several limitations that can be ameliorated in forthcoming studies. Therefore, the findings of this study may serve as guidelines for the development of a more accurate spinal deformity assessment method that can aid medical personnel in the real diagnosis of scoliosis.
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