MELA dataset is a benchmark for developing algorithms on mediastinal lesion analysis. We hope this large-scale dataset could facilitate the research and application of automatic mediastinal lesion detection and diagnosis. MELA dataset contains 1100 CT scans collected from patients with one or more lesions in the mediastinum. The MELA dataset is split into a subset of 770 CT scans for training, a subset of 110 CT scans for validation, and a test set of 220 CT scans for evaluation. Due to the size limit of zenodo.org, we split the MELA training set into 3 parts; this is the Training Set Part 1 of MELA dataset, including 260 CTs. Files include: Train1.zip: 130 CTs in NII format (nii.gz). Train2.zip: 130 CTs in NII format (nii.gz).