对多发性硬化症病变进行彩绘以提高脑图谱的登记性能

M. Farazi, Fahim Faisal, Zaied Zaman, S. Farhan
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引用次数: 18

摘要

多发性硬化症(MS)是一种中枢神经系统的炎症性自身免疫性疾病,主要损害白质(WM)和灰质(GM)的髓鞘层。髓鞘层的缺失(脱髓鞘)暴露出WM和GM,这在MRI脑部扫描中被视为病变。为了标准化地治疗和监测MS的进展,将患者的MRI脑扫描记录在脑图谱上。然而,在这个配准步骤中,MS病变会在输出变换中产生强烈的失真,从而在配准图像中产生偏差。在本文中,我们提出了一种新的图像绘制技术来减少这种偏差。图像修复是对图像数据中丢失或变质的部分进行重建的一种方法。我们对MS病变进行涂漆,使其看起来像健康组织,并将涂漆后的MS大脑与脑图谱相匹配,然后添加被掩盖的病变。为了评估我们提出的图像绘制算法的性能,我们采用了一个两步评估过程。首先,我们用我们提出的最先进的方法在3D MRI图像数据中绘制扭曲的2D图像和人工MS病变。其次,我们将绘制的大脑与地图集进行注册,并将其性能与地面事实进行比较。这两步评估表明,所提出的inpainted算法相对于其他最先进的方法表现更好,并且还提高了配准性能,并显着减少了先前由MS病变造成的偏差。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Inpainting multiple sclerosis lesions for improving registration performance with brain atlas
Multiple sclerosis (MS) is a inflammatory autoimmune disease of the central nervous system which damage the myelin layer of White Matter (WM) and Grey Matter (GM). The loss of myelin layer (demyelination) exposes the WM and GM, which is viewed as lesions in the MRI brain scans. To treat and monitor the progression of MS in standardized way, patient MRI brain scans are registered with brain atlas. However, in this registration step, the MS lesions create a strong distortion in the output transformation which creates a bias in registered image. In this paper, we propose a novel image inpainting technique to reduce such bias. Image inpainting is used to reconstruct the lost or deteriorated parts of image data. We inpaint the MS lesions to make it appear like healthy tissue and register this inpainted MS brain with the brain atlas, and add the masked lesions afterwards. To evaluate the performance of our proposed inpainting algorithm, we employ a two step evaluation process. Firstly, we inpaint distorted 2D images and artificial MS lesions in 3D MRI image data with our proposed and state-of-the-art methods. Secondly, we register the inpainted brain with an atlas and compare its performance with the ground truth. This two step evaluation indicates that the proposed inpainted algorithm performs comparatively better than other state-of-the-art methods and it also increases the registration performance and significantly reduces the bias previously created by the MS lesions.
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