Skip to content
DSML.KZ
Publications

Dataset · Zenodo · July 24, 2026

MSPE-Swin: Multi-Scale Patch Embedding for Robust SwinUNETR — Weights

A.A. Lonshchakov, Dmitrii Kaplun, Aleksandr Sinitca

Dmitry Kaplun
Open via DOI

Abstract

Pretrained model weights for MSPE-Swin: Multi-Scale Patch Embedding For Robust SwinUNETR. MSPE-Swin adapts Multi-Scale Patch Embedding to SwinUNETR by replacing only the patch embedding layer with a small set of resolution-specific patch kernels, leaving the encoder, the skip connections, and the decoder unchanged. This record contains the checkpoints for the pulmonary-vessel histology, ADE20K, and HVSMR-2.0 experiments, under both the frozen-backbone fine-tuning and the full mixed-resolution training regimes, together with the ablation checkpoints. Source code: https://github.com/Digiratory/SwinUNETR-MSPE

Advanced Neural Network ApplicationsMedical Image Segmentation TechniquesDomain Adaptation and Few-Shot LearningSwin UNETRpretrained model weightsADE20K

More by Dmitry Kaplun