A Large-Scale Coronal Mass Ejection Instance Segmentation Dataset with Catalog-Guided Selection and Two-Stage Human Refinement

CME-Seg-LASCO is a curated LASCO C2 coronal mass ejection (CME) instance segmentation dataset constructed from CDAW catalog-guided event selection and two-stage human refinement. The dataset contains 12,740 image-annotation pairs from 1,501 CME events observed between 2002 and 2023. Each sample includes a standardized 8-bit running-difference PNG image, a final refined LabelMe polygon annotation in JSON format, and a corresponding rasterized binary mask PNG. Files are organized hierarchically by year and event, preserving temporal order for sequence-based learning. The dataset is designed to support benchmarking and training of single-frame and sequence-based CME segmentation and tracking models, and includes events spanning narrow, limb, partial-halo, and full-halo CME categories. Revision note This record was updated during peer review following a dataset-wide audit. The revised release contains 1,501 CME events and 12,740 image-annotation pairs. Nested event-directory cases were corrected, duplicate/ineligible events were removed where applicable, and one valid independent event was restored to its correct directory. Catalog-derived metadata in event_stats.csv were also re-audited and corrected for co-temporal CDAW CME entries, including Central_PA, MPA, Width, Category, and QUALITY_INDEX. The dataset-selection criteria were unchanged.