Enhanced multi-modal abdominal image registration via structural awareness and region-specific optimization

Abstract

Multi-modal abdominal image registration is a critical step in achieving accurate diagnosis and treatment. However, the large field of view, complex organ structures, and significant anatomical variability in the abdominal region pose substantial challenges to precise multi-modal registration. To address these challenges, we propose a novel framework based on structural awareness and region-specific optimization, which progressively enhances registration accuracy through a hierarchical strategy. The core innovation lies in introducing the Modality Independent Structural Awareness (MISA) loss, which comprises two key components: first, it ensures structural consistency across modalities by deeply understanding the critical anatomical structures; second, it employs a region-specific weighting strategy to prioritize key anatomical regions, such as organ boundaries, thereby achieving high-precision, region-specific constraints in multi-modal registration. Experimental results demonstrate that our method outperforms state-of-the-art approaches on two public multi-modal abdominal datasets, particularly in accurately capturing complex anatomical structures and maintaining tissue consistency. Further analysis confirms that the MISA loss and its two innovative components are pivotal in enhancing multi-modal abdominal image registration accuracy.