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Found 2 papers, 1 papers with code
Leveraging Semantic Asymmetry for Precise Gross Tumor Volume Segmentation of Nasopharyngeal Carcinoma in Planning CT
% In this study, we propose a novel approach to directly segment NPC gross tumors on non-contrast planning CT images, circumventing potential registration errors when aligning MRI or MRI-derived tumor masks to planning CT. To address the low contrast issues between tumors and adjacent normal structures in planning CT, we introduce a 3D Semantic Asymmetry Tumor segmentation (SATs) method.
IIRP-Net: Iterative Inference Residual Pyramid Network for Enhanced Image Registration
We conduct extensive experiments on the FLARE and Mindboggle datasets and the results verify the effectiveness of the proposed method outperforming state-of-the-art deformable image registration methods.
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