The dataset in laryngeal dataset.tar contains 1320 patches of healthy and early-stage cancerous laryngeal tissues. The patches (100x100 pixels) were manually extracted from 33 narrow-band laryngoscopic images of 33 different patients affected by laryngeal spinocellular carcinoma (diagnosed after histopathological examination). Specifically, four tissue classes were considered (330 patches/tissue class): He (healthy tissue), Hbv (tissue with hypertrophic vessels), Le (tissue with leukoplakia) and IPCL (tissue with intrapapillary capillary loops). The dataset was created for testing the method proposed in Moccia, Sara, et al. "Confident texture-based laryngeal tissue classification for early stage diagnosis support." JOURNAL OF MEDICAL IMAGING 4.03 (2017): 1-10. The folder laryngeal dataset.tar contains 3 subfolders (FOLD 1, FOLD 2, FOLD 3), which are the 3 folds used for cross-validation purpose in the tissue classification performance assessment. Each subfolder contains 4 folders relative to the four tissue classes, i.e., Le, He, Hbv, IPCL. ---------------------------------------------------------------------------------------------------------------------------------------------------------- If you want to use the dataset, please cite Moccia, Sara, et al. "Confident texture-based laryngeal tissue classification for early stage diagnosis support." JOURNAL OF MEDICAL IMAGING 4.03 (2017): 1-10.