LASSNet: Level-Aware Availability-Conditioned Spatial-Semantic Fusion for Brain Tumor Segmentation with Missing MRI Modalities

2026-09-06

AI Summary

本文提出LASSNet，通过层次感知和模态可用性条件下的空间-语义融合方法解决MRI模态缺失情况下的脑肿瘤分割问题。

Abstract

Brain tumor segmentation from multimodal MRI relies on complementary evidence across four imaging sequences, yet one or more modalities may be unavailable because of acquisition cost, protocol variation, scan failure, or patient condition. Existing work has explored reconstruction, knowledge transfer, and direct feature fusion, but leaves open whether missing-modality fusion should change with representation level. High-resolution lateral features retain spatial detail, whereas compressed bottleneck features encode semantic and inter-modality context. We therefore hypothesize that fusion should be conditioned jointly on modality availability and feature hierarchy. We propose the Level-Aware Availability-Conditioned Spatial-Semantic Fusion Network (LASSNet), which contains two level-specialized modules. Hierarchical Availability-Conditioned Fusion (HACF) constructs four lateral representations using count-normalized aggregation of available modalities, mask-conditioned channel modulation, and local 3D refinement. Tri-Scale Relational-Spatial Fusion (TriRSF) models relations among available modality descriptors and spatial context across multiple bottleneck resolutions, followed by cross-scale aggregation and availability-conditioned global spatial attention. A shared coarse-to-fine decoder starts from TriRSF semantics and progressively injects HACF features, without reconstructing missing inputs. Across all 15 non-empty modality configurations, LASSNet obtains mean Dice scores of 76.7% and 83.2% over WT, TC, and ET on BraTS2019 and BraTS2023, respectively.

Problem

• Brain Tumor Segmentation
• Missing MRI Modalities
• Spatial-Semantic Fusion

Innovation

• Level-Aware Availability-Conditioned Fusion
• Hierarchical Availability-Conditioned Fusion (HACF)
• Tri-Scale Relational-Spatial Fusion (TriRSF)