Multi-modal Magnetic Resonance Imaging (MRI) is imperative for accurate brain tumor segmentation, offering indispensable complementary information. Nonetheless, the absence of modalities poses significant challenges in achieving precise segmentation. Recognizing the shared anatomical structures between mono-modal and multi-modal representations, it is noteworthy that mono-modal images typically exhibit limited features in specific regions and tissues. In response to this, we present Anatomical Consistency Distillation and Inconsistency Synthesis (ACDIS), a novel framework designed to transfer anatomical structures from multi-modal to mono-modal representations and synthesize modality-specific features. ACDIS consists of two main components: Anatomical Consistency Distillation (ACD) and Modality Feature Synthesis Block (MFSB). ACD incorporates the Anatomical Feature Enhancement Block …
本文提出ACDIS框架，用于解决脑肿瘤分割中MRI模态缺失的问题。通过解剖一致性蒸馏将多模态图像中的共享解剖结构迁移至单模态表示，并利用模态特征合成块生成模态特定特征，从而增强单模态图像在特定区域的组织表现。该方法有效缓解了模态缺失带来的性能下降，提升了分割精度。