CeraMIRScan: Mid-infrared OCT Scan Dataset for Ceramic Quality Assessment

Mid-infrared Optical Coherence Tomography (MIR-OCT) is a promising Non-Destructive Testing (NDT) technique due to its high-resolution imaging capabilities and extensive applicability across various industrial domains. The CeraMIRScan dataset comprises 29 volumes corresponding to MIR-OCT scans of 3D printed ceramic pieces and has been carefully curated to support the development of Deep Learning models for defect segmentation. Of these, 22 volumes include bounding-box annotations to enable defect localisation and classification, while all volumes are accompanied by manually generated binary segmentation masks. In total, the dataset contains 21,882 individual scans, of which 41.38% exhibit detectable defects. The dataset is organised into three primary components. The first images/ contains the 29 MIR-OCT volumes. The second annotations/raw_labels/ provides bounding-box coordinates and defect-level labels for 22 volumes. The third annotations/masks/ includes pixel-wise segmentation masks for all volumes. Image and mask files follow the naming convention 'VolumeName_SlideNumber.png', and bounding-box annotations are stored as 'VolumeName.csv'.中红外光学相干断层扫描（Mid-infrared Optical Coherence Tomography，MIR-OCT）凭借高分辨率成像能力与跨多工业领域的广泛适用性，成为极具发展前景的无损检测（Non-Destructive Testing，NDT）技术。 CeraMIRScan数据集包含29组3D打印陶瓷件的MIR-OCT扫描体数据，经精心整理以支撑深度学习（Deep Learning）模型的缺陷分割研发工作。其中22组体数据带有边界框标注，可用于缺陷定位与分类任务；所有体数据均配套有人工生成的二值分割掩码。该数据集总计包含21882幅独立扫描图像，其中41.38%的图像存在可检测缺陷。 该数据集分为三个主要组成部分：第一部分为images/目录，存储全部29组MIR-OCT体数据；第二部分为annotations/raw_labels/目录，为22组体数据提供边界框坐标与缺陷层级标签；第三部分为annotations/masks/目录，包含所有体数据的逐像素分割掩码。图像与掩码文件均遵循"VolumeName_SlideNumber.png"的命名规范，边界框标注文件则以"VolumeName.csv"格式存储。