IntraStyler uses a contrastively trained style encoder to synthesize T2 MRI styles without predefined sub-domains, raising Extra-VS Dice from 0.61 to 0.81 with zero failures on CrossMoDA
The work proposes IntraStyler, a 3D unpaired image translation method that requires no predefined sub-domains, using a contrastively trained style encoder to extract anatomy-disentangled style embeddings from each target-domain image and conditioning a QS-Attn synthesis network via dynamic instance normalization; on the CrossMoDA benchmark (226 labeled ceT1, 295 unlabeled T2, 96-image T2 test set) it automatically discovers 7 style references instead of the 3 used by sub-domain methods, and downstream nnU-Net segmentation achieves the best Dice and ASSD on Intra-VS, Extra-VS, and Cochlea, with Extra-VS Dice of 0.81 and zero failures.