Methodology to Determine Important-Points Location for Automated Lumbar Spine Stenosis Diagnosis Procedure

F. Natalia, H. Meidia, N. Afriliana, A. Al-Kafri, S. Sudirman
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引用次数: 6

Abstract

Chronic Lower Back Pain (CLBP) is one of the major types of pain that is affecting many people around the world. Lumbar Spine Stenosis (LSS), a major cause of CLBP, requires experienced neuroradiologists to detect and diagnose. It has been reported that the number of MRI examinations around the world is increasing but the number of specialist neuroradiologists to examine and analyse them has not. This paper presents a continuation of our methodology to automatically detect the presence of LSS by analyzing lumbar spine MRI images. It details important points location-determination algorithm that can be further processed in the LSS diagnosis procedure. We use the results of our, previously developed, boundary delineation method to supply boundary points to the algorithm. The algorithm is applied to the best cut axial-view images of the intervertebral discs of 515 patients contained in the Lumbar Spine MRI dataset. The results of the important points locations are presented.
确定腰椎狭窄症自动诊断过程中重要点位置的方法学
慢性腰痛(CLBP)是影响世界各地许多人的主要疼痛类型之一。腰椎狭窄症(LSS)是CLBP的主要病因,需要经验丰富的神经放射学家来检测和诊断。据报道,世界各地核磁共振检查的数量正在增加,但检查和分析这些检查的神经放射专家的数量却没有增加。本文提出了我们的方法的延续,通过分析腰椎MRI图像自动检测LSS的存在。详细介绍了在LSS诊断过程中可进一步处理的重要点定位算法。我们使用之前开发的边界描绘方法的结果为算法提供边界点。该算法应用于腰椎MRI数据集中515例患者椎间盘的最佳轴向视图图像。给出了重要点位置的计算结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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