Junyin Xiong

DCLA-UNet: dynamic cross-layer compressive attention and large axial separable convolution for multi-modal MRI brain tumor segmentation

DCLA-UNet successfully breaks the conventional bottleneck of 3D global context modeling by achieving a competitive balance between parameter efficiency and segmentation accuracy and provides a robust, parameter-efficient solution for 3D medical image segmentation in storage-constrained clinical scenarios.