INTENSITY INHOMOGENEITY CORRECTION OF MACULAR OCT USING N3 AND RETINAL FLATSPACE.
INTENSITY INHOMOGENEITY CORRECTION OF MACULAR OCT USING N3 AND RETINAL FLATSPACE.
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DOI：
10.1109/isbi.2016.7493243
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发表时间：
2016-04
期刊：
影响因子：
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通讯作者：
Prince JL
中科院分区：
文献类型：
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作者：
Lang A;Carass A;Jedynak BM;Solomon SD;Calabresi PA;Prince JL
随着光学相干断层扫描 (OCT) 日益成为视网膜成像的标准方式，用于处理 OCT 数据的自动化算法已成为进行大规模研究寻找特定层变化的必要条件。为了提供准确的结果，许多算法依赖于扫描中层强度的一致性。不幸的是，OCT 数据通常在图像内部和图像之间的给定层强度上表现出不均匀性。这个问题会对分割算法的性能产生负面影响，并且之前几乎没有做任何工作来纠正这个数据。在这项工作中，我们采用了强度不均匀性校正的 N3 框架（最初是为校正 MRI 数据而开发的），以适用于黄斑 OCT 数据。我们首先将数据转换为平坦的黄斑空间，为每一层创建模板强度分布，从而为我们提供增益场的准确初始估计。然后，N3 将产生一个平滑变化的字段来纠正数据。我们表明，我们的方法既能够准确地恢复合成生成的增益场，又能够提高层强度的稳定性。
As optical coherence tomography (OCT) has increasingly become a standard modality for imaging the retina, automated algorithms for processing OCT data have become necessary to do large scale studies looking for changes in specific layers. To provide accurate results, many of these algorithms rely on the consistency of layer intensities within a scan. Unfortunately, OCT data often exhibits inhomogeneity in a given layer’s intensities, both within and between images. This problem negatively affects the performance of segmentation algorithms and little prior work has been done to correct this data. In this work, we adapt the N3 framework for intensity inhomogeneity correction, which was originally developed to correct MRI data, to work for macular OCT data. We first transform the data to a flattened macular space to create a template intensity profile for each layer giving us an accurate initial estimate of the gain field. N3 will then produce a smoothly varying field to correct the data. We show that our method is able to both accurately recover synthetically generated gain fields and improves the stability of the layer intensities.