一种新的CBCT图像TMJ对比度增强算法。

IF 0.9 Q4 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Acta radiologica open Pub Date : 2022-02-17 eCollection Date: 2022-01-01 DOI:10.1177/20584601221074565
María Florinda Otero, Pablo García Tahoces, Antonio Mera, Jorge Mira
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引用次数: 1

摘要

磁共振成像(MRI)被认为是可靠诊断幼年特发性关节炎(JIA)患者颞下颌关节(TMJ)炎症的金标准。然而,即使是MRI成像也依赖于放射科医生对TMJ正常外观的熟悉程度;因此,需要新的方法。我们的目的是提高锥形束计算机断层扫描(CBCT)的成像质量,以帮助诊断颞下颌关节的JIA。我们设计并应用了一个滤波器(堆叠增强滤波器),对来自两名JIA患者tmj的CBCT图像进行处理。然后,我们将结果与同一患者的核磁共振成像档案图像进行了视觉比较,以表明过滤器大大提高了图像的视觉质量。在图像对比度和不同密度的组织(关节内存在的所有解剖结构)之间外观差异的增加方面的工作导致在不使用化学造影剂的情况下改善TMJ的最终图像。我们认为CBCT可以作为一种过滤工具来分析受关节炎影响的颞下颌关节。我们的图像处理技术产生的图像可能会提高CBCT的使用范围。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

TMJ contrast enhancement in CBCT images using a new algorithm.

TMJ contrast enhancement in CBCT images using a new algorithm.

TMJ contrast enhancement in CBCT images using a new algorithm.

TMJ contrast enhancement in CBCT images using a new algorithm.

Magnetic resonance imaging (MRI) is considered the gold standard to reliably diagnose inflammation in the temporomandibular joint (TMJ) of patients with juvenile idiopathic arthritis (JIA). However, even MRI imaging is dependent on the familiarity of the radiologist with the normal appearance of the TMJ; therefore, new approaches are needed. Our purpose here is to improve imaging quality of cone beam computed tomography (CBCT) as a tool to help in the diagnosis of JIA in the TMJ. We have designed and applied a filter (the Stacking Enhancement Filter) over a stock of CBCT images from the TMJs of two patients with JIA. We then made a visual comparison of the results with archival images from MRI of the same patients, to show that the filter substantially improves the visual quality of the image. The work on the image contrast and the increase of the difference of appearance between tissues of different densities (all the anatomical structures that are present within the joint) leads to an improvement of the resulting images of the TMJ without the use of a chemical contrast agent. We conclude that CBCT could be used as a filter tool for the analysis of the TMJs affected by arthritis. Our image processing technique yields images that possible improve the range of use of CBCT.

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