References

  • Curti N, Merli Y, Zengarini C, Giampieri E, Merlotti A, Dall’Olio D, Marcelli E, Bianchi T, Castellani G. Effectiveness of Semi-Supervised Active Learning in Automated Wound Image Segmentation. International Journal of Molecular Sciences. 2023; 24(1):706. https://doi.org/10.3390/ijms24010706

  • Buschi D, Curti N, Cola V, Carlini G, Sala C, Dall’Olio D, Castellani G, Pizzi E, Del Magno S, Foglia A, et al. Automated Wound Image Segmentation: Transfer Learning from Human to Pet via Active Semi-Supervised Learning. Animals. 2023; 13(6):956. https://doi.org/10.3390/ani13060956

  • Amparo F, Wang H, Emami-Naeini P, Karimian P, Dana R. The Ocular Redness Index: a novel automated method for measuring ocular injection. Invest Ophthalmol Vis Sci. 2013 Jul 18;54(7):4821-6. doi: 10.1167/iovs.13-12217. PMID: 23766472; PMCID: PMC3720148.

  • Park IK, Chun YS, Kim KG, Yang HK, Hwang JM. New clinical grading scales and objective measurement for conjunctival injection. Invest Ophthalmol Vis Sci. 2013 Aug 5;54(8):5249-57. doi: 10.1167/iovs.12-10678. PMID: 23833063.

  • Curti N, Giampieri E, Guaraldi F, Bernabei F, Cercenelli L, Castellani G, Versura P, Marcelli E. A Fully Automated Pipeline for a Robust Conjunctival Hyperemia Estimation. Applied Sciences. 2021; 11(7):2978. https://doi.org/10.3390/app11072978.