AMDI Myocardial Infarction Dataset
Description
This dataset provides late gadolinium enhancement cardiac magnetic resonance (LGE-CMR) images for the study of myocardial infarction (MI) analysis. The dataset was compiled to support the development and evaluation of image analysis methods including segmentation, intensity-based representation, and visualization of infarcted myocardial tissue. The data consist of 2D short-axis LGE-MRI images acquired retrospectively from 25 patients using a 3.0T MRI scanner. Two reconstruction types are included for each slice: magnetization-prepared inversion recovery (MR-IR) and conventional inversion recovery (CR-IR), providing variations in contrast distribution for the same anatomical location. All images are converted from DICOM to 16-bit TIFF format using DICOM rescale slope and intercept parameters to preserve the original intensity information. Three primary data components were provided. First, raw LGE-MRI images are provided without windowing or levelling, allowing users to apply custom preprocessing at their need. Second, a manually delineate and radiologist-verified multi-class segmentation ground truth masks are included with four RGB encoded class representing left ventricle myocardium, cavity, scar, and background. Third, intensity-encoded ground truth (IEGT) images are provided, where infarction regions are enhanced while preserving anatomical structure. IEGT were generated through a sequence of preprocessing steps including contrast normalization, unbiased non-local means denoising, contrast refinement via histogram matching, and mask guided intensity encoding. Additional supporting files included slice-level metadata in .csv format extracted from DICOM headers, and radiological reports in .pdf format describing patient-level findings. Dataset is organized at patient and slice levels with consistent naming conventions, enabling direct pairing between raw images, segmentation masks, and provided outputs. The dataset provides a structured resource for investigating both anatomical and intensity-based representation of myocardial infarction in LGE-CMR imaging.
Files
Steps to reproduce
Original source code and supplementary materials detailing the preprocessing steps in showing reproducibility are provided via GitHub repository link.
Institutions
- Universiti Teknologi MARASelangor, Shah Alam
- Universiti Sains MalaysiaPenang, George Town