Improve Cross-Modality Segmentation by Treating MRI Images as Inverted CT Scans
arxiv(2024)
摘要
Computed tomography (CT) segmentation models frequently include classes that
are not currently supported by magnetic resonance imaging (MRI) segmentation
models. In this study, we show that a simple image inversion technique can
significantly improve the segmentation quality of CT segmentation models on MRI
data, by using the TotalSegmentator model, applied to T1-weighted MRI images,
as example. Image inversion is straightforward to implement and does not
require dedicated graphics processing units (GPUs), thus providing a quick
alternative to complex deep modality-transfer models for generating
segmentation masks for MRI data.
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