CXR-LT: Multi-Label Long-Tailed Classification on Chest X-Rays

Chest radiography presents a "long-tailed" distribution of findings, where a
few diseases are common, but most are rare. Diagnosis is further complicated
by its multi-label nature, as patients often exhibit multiple co-occurring
findings. While recent research has attempted to address the long-tailed
medical image classification problem, the interplay between class imbalance
and label co-occurrence remains underexplored. The **CXR-LT 2024 challenge**
builds on the success of CXR-LT 2023, expanding the dataset of 377,110 chest
X-rays (CXRs) to 45 disease labels, including 19 new rare disease findings.
This year 's challenge introduces three tasks: (i) long-tailed classification
on a large, noisy test set, (ii) long-tailed classification on a manually
annotated "gold standard" subset, and (iii) zero-shot generalization to five
previously unseen disease findings. CXR-LT 2024 addresses critical challenges
in long-tailed, multi-label, and zero-shot learning for medical imaging by
synthesizing state-of-the-art solutions from the international research
community. Further, our dataset contributions -- expanding disease coverage to
better reflect real-world clinical settings -- offer a valuable resource for
future research. This project contains labels from the CXR-LT 2024 and CXR-LT
2023 challenges, as well as a related subset used in the MICCAI 2023 paper,
"How Does Pruning Impact Multi-Label Long-Tailed Learning?"

胸部放射影像（Chest radiography）的检出结果呈现“长尾（long-tailed）分布”：少数疾病较为常见，而绝大多数病症则属于罕见范畴。由于患者往往同时存在多种并发检出结果，胸部影像诊断的多标签（multi-label）特性进一步加剧了任务复杂度。尽管现有研究已尝试解决长尾医学图像分类问题，但类别不平衡与标签共现之间的交互机制仍未得到充分探索。**CXR-LT 2024挑战赛**承接CXR-LT 2023的成功经验，将原有的377,110张胸部X线（Chest X-rays, CXR）数据集拓展至45种疾病标签，其中包含19种新增的罕见病症检出结果。本届挑战赛设置三项任务：(i) 基于大规模带噪测试集的长尾分类任务；(ii) 基于人工标注“金标准”子集的长尾分类任务；(iii) 针对5种未见过的全新病症的零样本（Zero-shot）泛化任务。CXR-LT 2024挑战赛通过整合国际研究社群的前沿解决方案，针对性解决医学影像领域中长尾、多标签以及零样本学习的核心挑战。此外，本数据集通过拓展疾病覆盖范围以更贴合真实临床场景，为后续研究提供了极具价值的研究资源。本项目包含CXR-LT 2024与CXR-LT 2023挑战赛的标签数据，以及MICCAI 2023论文《剪枝如何影响多标签长尾学习？》中使用的相关子集。