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Magnetic Resonance Image Example-Based Contrast Synthesis

机译：基于磁共振图像实例的对比度合成

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摘要

The performance of image analysis algorithms applied to magnetic resonance images is strongly influenced by the pulse sequences used to acquire the images. Algorithms are typically optimized for a targeted tissue contrast obtained from a particular implementation of a pulse sequence on a specific scanner. There are many practical situations, including multi-institution trials, rapid emergency scans, and scientific use of historical data, where the images are not acquired according to an optimal protocol or the desired tissue contrast is entirely missing. This paper introduces an image restoration technique that recovers images with both the desired tissue contrast and a normalized intensity profile. This is done using patches in the acquired images and an atlas containing patches of the acquired and desired tissue contrasts. The method is an example-based approach relying on sparse reconstruction from image patches. Its performance in demonstrated using several examples, including image intensity normalization, missing tissue contrast recovery, automatic segmentation, and multimodal registration. These examples demonstrate potential practical uses and also illustrate limitations of our approach.
机译：应用于磁共振图像的图像分析算法的性能在很大程度上受到用于采集图像的脉冲序列的影响。通常针对从特定扫描仪上的脉冲序列的特定实现获得的目标组织对比度优化算法。存在许多实际情况，包括多机构试验，快速紧急扫描和历史数据的科学使用，在这些情况下，无法根据最佳方案获取图像或完全缺少所需的组织对比度。本文介绍了一种图像恢复技术，该技术可恢复具有所需组织对比度和归一化强度分布的图像。使用获取的图像中的补丁和包含获取的和所需组织对比的补丁的图集来完成此操作。该方法是基于示例的方法，依赖于从图像补丁进行稀疏重建。使用几个示例演示了它的性能，包括图像强度归一化，丢失组织对比度恢复，自动分割和多模式配准。这些示例说明了潜在的实际用途，也说明了我们方法的局限性。

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