Multi-Contrast MRI Segmentation Trained on Synthetic Images.
Multi-Contrast MRI Segmentation Trained on Synthetic Images.
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基于合成图像训练的多对比MRI分割。
DOI：
10.1109/embc48229.2022.9871119
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发表时间：
2022-07
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在我们的综合实验和评估中，我们表明可以生成多个对比度（甚至全部合成），并使用合成生成的图像来训练图像分割引擎。我们在描绘肌肉、脂肪、骨骼和骨髓时，在真实的多对比度MRI扫描上测试了有希望的分割结果，所有这些都是在合成图像上训练的。基于合成图像训练，我们的分割结果高达93.91%，94.11%，91.63%，95.33%，肌肉，脂肪，骨骼和骨髓描绘分别。结果与使用真实的图像进行分割训练时获得的结果无显著差异：分别为94.68%、94.67%、95.91%和96.82%。
In our comprehensive experiments and evaluations, we show that it is possible to generate multiple contrast (even all synthetically) and use synthetically generated images to train an image segmentation engine. We showed promising segmentation results tested on real multi-contrast MRI scans when delineating muscle, fat, bone and bone marrow, all trained on synthetic images. Based on synthetic image training, our segmentation results were as high as 93.91%, 94.11%, 91.63%, 95.33%, for muscle, fat, bone, and bone marrow delineation, respectively. Results were not significantly different from the ones obtained when real images were used for segmentation training: 94.68%, 94.67%, 95.91%, and 96.82%, respectively.