Image harmonization improves consistency of intra-rater delineations of MS lesions in heterogeneous MRI

Q4 Neuroscience
Aaron Carass , Danielle Greenman , Blake E. Dewey , Peter A. Calabresi , Jerry L. Prince , Dzung L. Pham
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引用次数: 0

Abstract

Clinical magnetic resonance images (MRIs) lack a standard intensity scale due to differences in scanner hardware and the pulse sequences used to acquire the images. When MRIs are used for quantification, as in the evaluation of white matter lesions (WMLs) in multiple sclerosis, this lack of intensity standardization becomes a critical problem affecting both the staging and tracking of the disease and its treatment. This paper presents a study of harmonization on WML segmentation consistency, which is evaluated using an object detection classification scheme that incorporates manual delineations from both the original and harmonized MRIs. A cohort of ten people scanned on two different imaging platforms was studied. An expert rater, blinded to the image source, manually delineated WMLs on images from both scanners before and after harmonization. It was found that there is closer agreement in both global and per-lesion WML volume and spatial distribution after harmonization, demonstrating the importance of image harmonization prior to the creation of manual delineations. These results could lead to better truth models in both the development and evaluation of automated lesion segmentation algorithms.

图像协调提高了多发性硬化症病变在异质磁共振成像中评分者内部划分的一致性
由于扫描仪硬件和用于获取图像的脉冲序列不同,临床磁共振图像(MRI)缺乏标准的强度标度。当磁共振成像用于量化时,如评估多发性硬化症的白质病变(WMLs),这种强度标准化的缺乏就成为影响疾病分期、跟踪和治疗的关键问题。本文介绍了一项关于白质病变分割一致性的协调研究,该研究使用对象检测分类方案进行评估,该方案结合了原始磁共振成像和协调磁共振成像的手动划分。研究对象包括在两种不同成像平台上扫描的十个人。一位对图像来源视而不见的专家评分员在协调前后对两台扫描仪的图像进行了 WML 人工划线。结果发现,在协调后,全球和每个病灶的 WML 体积和空间分布都更加一致,这说明了在创建手动划界之前进行图像协调的重要性。这些结果可以为自动病灶分割算法的开发和评估提供更好的真相模型。
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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来源期刊
Neuroimage. Reports
Neuroimage. Reports Neuroscience (General)
CiteScore
1.90
自引率
0.00%
发文量
0
审稿时长
87 days
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