MELA Dataset: A Benchmark for Mediastinal Lesion Analysis (Training Set Part 3)

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 3 of MELA dataset, including 250 CTs. Files include: Train5.zip: 130 CTs in NII format (nii.gz). Train6.zip: 120 CTs in NII format (nii.gz).MELA数据集是一款面向纵隔病变分析算法研发的基准数据集。我们期望该大规模数据集能够推动自动化纵隔病变检测与诊断领域的研究与应用发展。MELA数据集共收录1100例来自纵隔存在一处或多处病变患者的CT扫描数据。该数据集被划分为三个子集：用于模型训练的770例CT扫描训练子集、用于模型验证的110例CT扫描验证子集，以及用于模型性能评估的220例CT扫描测试子集。鉴于zenodo.org平台的文件大小限制，我们将MELA训练集拆分为三个子部分；本次发布的为MELA数据集训练集第三部分，共包含250例CT扫描数据。本次发布的文件包括：Train5.zip：130例NII格式（NII）的CT扫描数据，以nii.gz格式压缩；Train6.zip：120例NII格式（NII）的CT扫描数据，以nii.gz格式压缩。