AI RESEARCH
RIHA: Report-Image Hierarchical Alignment for Radiology Report Generation
arXiv CS.AI
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ArXi:2604.27559v1 Announce Type: cross Radiology report generation (RRG) has emerged as a promising approach to alleviate radiologists' workload and reduce human errors by automatically generating diagnostic reports from medical images. A key challenge in RRG is achieving fine-grained alignment between complex visual features and the hierarchical structure of long-form radiology reports. Although recent methods have improved image-text representation learning, they often treat reports as flat sequences, overlooking their structured sections and semantic hierarchies.