Search Results for author:
Found 2 papers, 0 papers with code
A 3D Multi-Style Cross-Modality Segmentation Framework for Segmenting Vestibular Schwannoma and Cochlea
The crossMoDA2023 challenge aims to segment the vestibular schwannoma (sub-divided into intra- and extra-meatal components) and cochlea regions of unlabeled hrT2 scans by leveraging labeled ceT1 scans.
An Unpaired Cross-modality Segmentation Framework Using Data Augmentation and Hybrid Convolutional Networks for Segmenting Vestibular Schwannoma and Cochlea
We adopt two data augmentation methods for effectively learning the semantic information and generating realistic target domain scans: generative and online data augmentation.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
