References
- Cha D, Pae C, Seong S-B, et al. Automated diagnosis of ear disease using ensemble deep learning with a big otoendoscopy image database. EBioMedicine. 2019;45:606–614.
- Lee JY, Choi S-H, Chung JW. Automated classification of the tympanic membrane using a convolutional neural network. Applied Sciences. 2019;9(9):1827.
- Kinney SE. Five years experience using the intact canal wall tympanoplasty with mastoidectomy for cholesteatoma: preliminary report. Laryngoscope. 1982;92(12):1395–1400.
- Kozin ED, Gulati S, Kaplan AB, et al. Systematic review of outcomes following observational and operative endoscopic Middle ear surgery. Laryngoscope. 2015;125(5):1205–1214.
- Migirov L, Shapira Y, Horowitz Z, et al. Exclusive endoscopic ear surgery for acquired cholesteatoma: preliminary results. Otol Neurotol. 2011;32(3):433–436.
- Barnes J, Sabo RT, Coelho DH. A novel method to measure the external auditory canal: normative data and practical implications. Am J Otolaryngol. 2018;39(2):146–149.
- Dedmon MM, O’Connell BP, Kozin ED, et al. Development and validation of a modular endoscopic ear surgery skills trainer. Otol Neurotol. 2017;38(8):1193–1197.
- Edmond CV. Impact of the endoscopic sinus surgical simulator on operating room performance. Laryngoscope. 2002;112(7 Pt 1):1148–1158.
- Woods A, Lagravère MO. Three-dimensional changes of the auditory canal in a three-year period during adolescence using CBCTs. Int J Dent. 2018;2018:1–10.
- Lambin P, Leijenaar RTH, Deist TM, et al. Radiomics: the bridge between medical imaging and personalized medicine. Nat Rev Clin Oncol. 2017;14(12):749–762.
- Remeseiro B, Bolon-Canedo V. A review of feature selection methods in medical applications. Comput Biol Med. 2019;112:103375.
- Halder A, Chatterjee N, Kar A, et al. editors. Edge detection: a statistical approach. 2011 3rd International Conference on Electronics Computer Technology; 2011. IEEE.
- Van Griethuysen JJ, Fedorov A, Parmar C, et al. Computational radiomics system to decode the radiographic phenotype. Cancer Res. 2017;77(21):e104–e7.
- Gillies RJ, Kinahan PE, Hricak H. Radiomics: images are more than pictures, they are data. Radiology. 2016;278(2):563–577.
- Arendt CT, Leithner D, Mayerhoefer ME, et al. Radiomics of high-resolution computed tomography for the differentiation between cholesteatoma and Middle ear inflammation: effects of post-reconstruction methods in a dual-center study. Eur Radiol. 2021;31(6):4071–4078.
- Ito T, Kubota T, Furukawa T, et al. Measurement of the pediatric and adult osseous external auditory canal: implications for transcanal endoscopic ear surgery. Otol Neurotol. 2020;41(6):e712–e9.
- Ito T, Kubota T, Watanabe T, et al. Transcanal endoscopic ear surgery for pediatric population with a narrow external auditory canal. Int J Pediatr Otorhinolaryngol. 2015;79(12):2265–2269.
- Peltonen L, Aarnisalo A, Kortesniemi M, et al. Limited cone-beam computed tomography imaging of the Middle ear: a comparison with multislice helical computed tomography. Acta Radiol. 2007;48(2):207–212.
- Chan HH, Siewerdsen JH, Vescan A, et al. 3D rapid prototyping for otolaryngology—head and neck surgery: applications in image-guidance, surgical simulation and patient-specific modeling. PLoS One. 2015;10(9):e0136370.
- Baghdadi A, Hussein AA, Ahmed Y, et al. A computer vision technique for automated assessment of surgical performance using surgeons’ console-feed videos. Int J Comput Assist Radiol Surg. 2019;14(4):697–707.