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.