Angiographic Report Generation for the 3rd APTOS’s Competition: Dataset and Baseline Methods

Weiyi Zhang, Peranut Chotcomwongse, Xiaolan Chen, Florence H.T. Chung, Fan Song, Xueli Zhang, Mingguang He, Danli Shi, Paisan Ruamviboonsuk
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Abstract

Fundus angiography, including fundus fluorescein angiography (FFA) and indocyanine green angiography (ICGA), are essential examination tools for visualizing lesions and changes in retinal and choroidal vasculature. However, the interpretation of angiography images is labor-intensive and time-consuming. In response to this, we are organizing the third APTOS competition for automated and interpretable angiographic report generation. For this purpose, we have released the first angiographic dataset, which includes over 50,000 images labeled by retinal specialists. This dataset covers 24 conditions and provides detailed descriptions of the type, location, shape, size and pattern of abnormal fluorescence to enhance interpretability and accessibility. Additionally, we have implemented two baseline methods that achieve an overall score of 7.966 and 7.947 using the classification method and language generation method in the test set, respectively. We anticipate that this initiative will expedite the application of artificial intelligence in automatic report generation, thereby reducing the workload of clinicians and benefiting patients on a broader scale.
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第三届APTOS竞赛的血管造影报告生成:数据集和基线方法
眼底血管造影,包括眼底荧光素血管造影(FFA)和吲哚菁绿血管造影(ICGA),是观察视网膜和脉络膜血管病变和变化的基本检查工具。然而,血管造影图像的解释是劳动密集型和耗时的。为此,我们正在组织第三届APTOS自动和可解释的血管造影报告生成竞赛。为此,我们发布了第一个血管造影数据集,其中包括超过50,000张由视网膜专家标记的图像。该数据集涵盖了24种情况,并提供了异常荧光的类型、位置、形状、大小和模式的详细描述,以增强可解释性和可访问性。此外,我们在测试集中使用分类方法和语言生成方法实现了两种基线方法,分别获得了7.966和7.947的总分。我们预计这一举措将加快人工智能在自动报告生成中的应用,从而减少临床医生的工作量,并在更大范围内使患者受益。
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