Field-of-view (FOV) recovery of truncated chest CT scans is crucial for accurate body composition analysis, which involves quantifying skeletal muscle and subcutaneous adipose tissue (SAT) on CT slices. This, in turn, enables disease prognostication. Here, we present a method for recovering truncated CT slices using generative image outpainting. We train a diffusion model and apply it to truncated CT slices generated by simulating a small FOV. Our model reliably recovers the truncated anatomy and outperforms the previous state-of-the-art despite being trained on 87% less data.

翻译：胸部CT扫描的视野（FOV）恢复对于精确的身体成分分析至关重要，该分析涉及量化CT切片上的骨骼肌和皮下脂肪组织（SAT）。这进而有助于疾病预后。本文提出了一种利用生成式图像外延技术恢复截断CT切片的方法。我们训练了一个扩散模型，并将其应用于通过模拟小FOV生成的截断CT切片。我们的模型能够可靠地恢复被截断的解剖结构，尽管训练数据量减少了87%，但其性能仍优于先前的最先进方法。