Combining neural networks and image synthesis to enable automatic thoracic cavity segmentation of hyperpolarized 129Xe MRI without proton scans
S Leewiwatwong, J Lu, I Dummer, K Yarnall… - Magnetic Resonance …, 2023 - Elsevier
Rationale and objectives Quantification of 129 Xe MRI relies on accurate segmentation of
the thoracic cavity, typically performed manually using a combination of 1 H and 129 Xe
scans. This can be accelerated by using Convolutional Neural Networks (CNNs) that
segment only the 129 Xe scan. However, this task is complicated by peripheral ventilation
defects, which requires training CNNs with large, diverse datasets. Here, we accelerate the
creation of training data by synthesizing 129 Xe images with a variety of defects. We use this …
the thoracic cavity, typically performed manually using a combination of 1 H and 129 Xe
scans. This can be accelerated by using Convolutional Neural Networks (CNNs) that
segment only the 129 Xe scan. However, this task is complicated by peripheral ventilation
defects, which requires training CNNs with large, diverse datasets. Here, we accelerate the
creation of training data by synthesizing 129 Xe images with a variety of defects. We use this …
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