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English(EN) RIHA: Report-Image Hierarchical Alignment for Radiology Report Generation

RIHA Transformer 通过分层对齐放射科图像和报告，实现更好的生成效果

作者 PulseAugur 编辑部 · [2 个来源] ·

研究人员开发了RIHA，一个新颖的放射科报告生成框架，解决了将复杂视觉特征与医学报告的分层结构对齐的挑战。与先前将报告视为扁平序列的方法不同，RIHA在段落、句子和单词之间执行多级对齐。这种分层方法利用视觉特征金字塔和文本特征金字塔，通过跨模态分层对齐模块进行集成，实现了图像和文本之间更精确的映射。在IU-Xray和MIMIC-CXR等基准数据集上的实验表明，RIHA在自然语言生成和临床疗效方面均优于现有的最先进模型。 AI

影响 通过增强跨模态对齐，提高了从医学图像生成诊断报告的准确性。

排序理由 介绍放射科报告生成新方法的学术论文。

在 arXiv cs.CV 阅读 →

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

RIHA Transformer 通过分层对齐放射科图像和报告，实现更好的生成效果

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报道来源 [2]

  1. arXiv cs.AI TIER_1 English(EN) · Yucheng Chen, Yang Yu, Yufei Shi, Conghao Xiong, Xulei Yang, Si Yong Yeo ·

    RIHA：放射科报告生成中的报告-图像分层对齐

    arXiv:2604.27559v1 Announce Type: cross Abstract: 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 achiev…

  2. arXiv cs.CV TIER_1 English(EN) · Si Yong Yeo ·

    RIHA：放射科报告生成中的报告-图像分层对齐

    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 …

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