English(EN) M\textsuperscript{4}Fuse: Lightweight State-Space MoE with a Cross-Scale Gating Bridge for Brain Tumor Segmentation

M4Fuse模型提供轻量级、高效的脑肿瘤分割

作者 PulseAugur 编辑部 · [2 个来源] · 2026-05-04 10:45

研究人员开发了M extsuperscript{4}Fuse，这是一种新颖的轻量级神经网络，用于脑肿瘤分割。该模型通过平衡编码器-解码器容量并采用协同设计，解决了现有方法的计算需求和脆弱性问题。它利用状态空间混合器进行长距离上下文传播，门控桥进行特征对齐，以及混合专家方法来提高鲁棒性。 AI

影响引入了一种更高效的医学图像分割模型，有望改进诊断工具。

排序理由这是一篇详细介绍特定任务新模型的学术论文。

AI 生成摘要 · Google Gemini · 来自 2 个来源。我们如何撰写摘要 →

报道来源 [2]

arXiv cs.CV TIER_1 English(EN) · Meihua Zhou, Xinyu Tong, Li Yang · 2026-05-05 04:00

M\textsuperscript{4}Fuse: Lightweight State-Space MoE with a Cross-Scale Gating Bridge for Brain Tumor Segmentation

arXiv:2605.02444v1 Announce Type: new Abstract: Encoder-decoder imbalance and the reliance on large input volumes make many 3D brain tumor segmentation models both compute-heavy and brittle. We present M\textsuperscript{4}Fuse, a lightweight network that prioritizes discriminativ…
arXiv cs.CV TIER_1 English(EN) · Li Yang · 2026-05-04 10:45

M\textsuperscript{4}Fuse: Lightweight State-Space MoE with a Cross-Scale Gating Bridge for Brain Tumor Segmentation

Encoder-decoder imbalance and the reliance on large input volumes make many 3D brain tumor segmentation models both compute-heavy and brittle. We present M\textsuperscript{4}Fuse, a lightweight network that prioritizes discriminative brain tumor cues over exhaustive appearance re…