Metadata for Simulated Brain Lesion Classification Tasks

The BrainLesion-15Class (100 Patients) dataset is a fully synthetic metadata collection representing 100 simulated brain MRI cases labeled with 15 real-world-inspired lesion types such as Glioma, Stroke, MS, and AVM. Each entry includes demographic info (age, gender), imaging modality (T1, T2, FLAIR, T1c), scan resolution, and scanner type. The dataset is ideal for machine learning tasks like multi-class classification, metadata filtering, and data stratification, while being completely privacy-safe and non-clinical.脑病变15分类（100名患者）数据集是一套全合成元数据集合，涵盖100例模拟脑部磁共振成像（Magnetic Resonance Imaging, MRI）病例，标注有胶质瘤（Glioma）、脑卒中（Stroke）、多发性硬化（Multiple Sclerosis, MS）、动静脉畸形（Arteriovenous Malformation, AVM）等15种贴合真实临床场景的病变类型。每条数据条目均包含人口统计学信息（年龄、性别）、成像模态（T1、T2、FLAIR、T1c）、扫描分辨率以及扫描仪类型。该数据集非常适用于多分类、元数据筛选及数据分层等机器学习任务，且完全符合隐私安全规范，无临床属性。