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| http://dx.doi.org/10.1016/j.healun.2025.01.015 | DOI Listing |
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School of Environmental and Biological Engineering, Nanjing University of Science and Technology, Nanjing 210094, China.
Accurate and automated segmentation of 3D biomedical images is a sophisticated imperative in clinical diagnosis, imaging-guided surgery, and prognosis judgment. Although the burgeoning of deep learning technologies has fostered smart segmentators, the successive and simultaneous garnering global and local features still remains challenging, which is essential for an exact and efficient imageological assay. To this end, a segmentation solution dubbed the mixed parallel shunted transformer (MPSTrans) is developed here, highlighting 3D-MPST blocks in a U-form framework.
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