A convolutional UNet without long-range sequence modeling beat Transformer and Mamba models on a new 204-patient colorectal tumor CT dataset.
The relevant baselines and all proposed architectures were trained on CTS- 204 for 200 epochs for the same learning rate and valida- tion interval
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Is Long Range Sequential Modeling Necessary For Colorectal Tumor Segmentation?
A convolutional UNet without long-range sequence modeling beat Transformer and Mamba models on a new 204-patient colorectal tumor CT dataset.