OpenMultiModalLiverCirrhosisDataset

The OpenMultiModalLiverCirrhosisDataset is a multi-modal medical imaging dataset designed for research in automated liver fibrosis staging and cirrhosis detection using artificial intelligence and machine learning techniques. The dataset contains 1,080 patient cases, each consisting of three imaging modalities: Magnetic Resonance Imaging (MRI) Computed Tomography (CT) Ultrasound (US) For each patient case, the dataset provides co-registered volumetric images along with structured clinical labels and metadata. Each sample includes: MRI liver image volume CT liver image volume Ultrasound liver image volume METAVIR fibrosis stage label (F0–F4) Binary cirrhosis label Patient age Patient sex Dataset split (train / validation / test) The dataset is intended for developing and benchmarking machine learning models for: liver fibrosis staging cirrhosis detection multimodal medical image analysis medical Vision Transformers deep learning for healthcare The images are provided as standardized volumetric arrays suitable for deep learning frameworks such as PyTorch and TensorFlow.OpenMultiModalLiverCirrhosisDataset是一款多模态医学影像数据集，旨在依托人工智能与机器学习技术开展自动化肝纤维化分期及肝硬化检测相关研究。 该数据集包含1080例患者病例，每例病例涵盖三种影像模态：磁共振成像（Magnetic Resonance Imaging，MRI）、计算机断层扫描（Computed Tomography，CT）与超声（Ultrasound，US）。 针对每一例患者病例，数据集均提供共配准体数据影像，以及结构化临床标签与元数据。 每个样本包含如下内容： 1. 肝脏磁共振成像体数据 2. 肝脏计算机断层扫描体数据 3. 肝脏超声体数据 4. METAVIR肝纤维化分期标签（F0–F4） 5. 二分类肝硬化标签 6. 患者年龄 7. 患者性别 8. 数据集划分（训练集/验证集/测试集） 本数据集可用于开发并基准测试适用于以下场景的机器学习模型： - 肝纤维化分期 - 肝硬化检测 - 多模态医学影像分析 - 医学视觉Transformer（Vision Transformer） - 医疗领域深度学习 影像以标准化体数组格式提供，可直接适配PyTorch、TensorFlow等深度学习框架。