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. 2025 Oct 8;19:1682603. doi: 10.3389/fnins.2025.1682603

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Copyright © 2025 Chen, Cai, Tan, Lv, Zhang and Du.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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Diagram showing a neural network architecture for image processing. Inputs include Flair, T1, T1ce, and T2 brain scans. A 5x5x5 convolution is applied, followed by three downsampling stages with SMW Conv modules. The process incorporates dilation convolution and context feature calibration. The upsampling flow includes gated attention mechanisms. A 1x1x1 convolution produces an output segmentation map. Modules are color-coded: SMW Conv (yellow), dilation and context calibration (green). Symbols indicate concatenation and gating steps. — MAUNet structure.