IBSU-1432 dataset on videoendoscopy frame quality classification for laryngoscopy (NBI modality)

<p><strong>How to cite</strong></p> <p>Nogal, P., Buchwald, M., Staśkiewicz, M., Kupiński, S., Pukacki, J., Mazurek, C., ... &amp; Wierzbicka, M. (2022). Endoluminal larynx anatomy model&ndash;towards facilitating deep learning and defining standards for medical images evaluation with artificial intelligence algorithms.&nbsp;<em>Polish Journal of Otolaryngology</em>,&nbsp;<em>76</em>(5), 37-45.&nbsp;<a href="https://doi.org/10.5604/01.3001.0015.9501">https://doi.org/10.5604/01.3001.0015.9501</a></p> <p>Paderno, A., Piazza, C., Del Bon, F., Lancini, D., Tanagli, S., Deganello, A., &hellip; Moccia, S. (2021). Deep Learning for Automatic Segmentation of Oral and Oropharyngeal Cancer Using Narrow Band Imaging: Preliminary Experience in a Clinical Perspective.&nbsp;<em>Frontiers in Oncology</em>,&nbsp;<em>11</em>(March), 1&ndash;12. <a href="https://doi.org/10.3389/fonc.2021.626602">https://doi.org/10.3389/fonc.2021.626602</a></p> <p>Moccia, S., Vanone, G. O., Momi, E. De, Laborai, A., Guastini, L., Peretti, G., &amp; Mattos, L. S. (2018). Learning-based classification of informative laryngoscopic frames.&nbsp;<em>Computer Methods and Programs in Biomedicine</em>,&nbsp;<em>158</em>, 21&ndash;30. <a href="https://doi.org/10.1016/j.cmpb.2018.01.030">https://doi.org/10.1016/j.cmpb.2018.01.030</a></p> <p><strong>Description</strong></p> <p>The presented dataset consists of&nbsp;1432 laryngeal endoscopy&nbsp;frames of different acquisition quality.&nbsp;The four classes were distinguished (after Moccia et al., 2018):</p> <ol> <li>Informative frames (436),</li> <li>Blurred (383),</li> <li>Saliva/specular reflections (321), and</li> <li>Underexposed frames (292).</li> </ol> <p>(In total, 1432 = 436 I + 383 B + 321 S + 292 U.)</p> <p><strong>Acknowledgements</strong></p> <p>Alberto Paderno, MD PhD&nbsp;&ndash; Brescia data part</p> <p>Sara Moccia, PhD &ndash;&nbsp;IBSU-720 frames dataset from Zenodo:&nbsp;<a href="https://zenodo.org/record/1162784#.Ycrmfi1Q1qt">https://zenodo.org/record/1162784#.Ycrmfi1Q1qt</a></p> <p>Małgorzata Wierzbicka, MD PhD&nbsp;&ndash; Poznan data part</p> <p>Piotr Nogal, MD&nbsp;&ndash; Poznan data part</p> <p>Joanna Jackowska, MD PhD&nbsp;&ndash; Poznan data part</p> <p>Hanna Klimza, MD PhD&nbsp;&ndash; Poznan data part</p>