DOCI Image Dataset

This dataset provides a comprehensive collection of multi-wavelength tissue images for the classification and analysis of thyroid cancer subtypes. The dataset is organized into four primary categories: Normal, Papillary, Anaplastic, and Follicular. Within each category, subfolders are structured by tissue name, ensuring clear organization for researchers. Each tissue-specific folder contains 23 images captured at different wavelengths, allowing for spectral analysis and feature extraction. Additionally, each folder includes at least one XML annotation file, which precisely defines the cancerous regions within the corresponding images. These annotations facilitate supervised learning tasks such as segmentation and classification. This dataset is a valuable resource for researchers developing machine learning models for thyroid cancer detection, spectral imaging analysis, and histopathological classification.