Yiheng Lyu

The work proposes TranSamba, which places a Cross-Plane Mamba (CPM) block before the Transformer block in every layer of a DeiT-S Vision Transformer encoder so that patch tokens in neighboring planes exchange information in linear time, improving in-plane self-attention and the class-to-patch attention maps; trained with only plane-level labels, 16 contiguous planes per volume and 16 volumes per batch for 100 epochs, it reaches 64.1%, 26.8% and 41.0% DSC and 46.8%, 25.8% and 25.6% IoU on the BraTS, KiTS and LASC test sets, the highest among the compared methods, with time complexity linear in the number of planes and batch space complexity independent of it.

The work proposes TranSamba, which places a Cross-Plane Mamba (CPM) block before the Transformer block in every layer of a DeiT-S Vision Transformer encoder so that patch tokens in neighboring planes exchange information in linear time, improving in-plane self-attention and the class-to-patch attention maps; trained with only plane-level labels, 16 contiguous planes per volume and 16 volumes per batch for 100 epochs, it reaches 64.1%, 26.8% and 41.0% DSC and 46.8%, 25.8% and 25.6% IoU on the BraTS, KiTS and LASC test sets, the highest among the compared methods, with time complexity linear in the number of planes and batch space complexity independent of it.