Deep Learning Techniques and Imaging in Otorhinolaryngology-A State-of-the-Art Review

被引:2
作者
Tsilivigkos, Christos [1 ]
Athanasopoulos, Michail [2 ]
di Micco, Riccardo [3 ]
Giotakis, Aris [1 ]
Mastronikolis, Nicholas S. [2 ]
Mulita, Francesk [4 ]
Verras, Georgios-Ioannis [4 ]
Maroulis, Ioannis [4 ]
Giotakis, Evangelos [1 ]
机构
[1] Natl & Kapodistrian Univ Athens, Hippocrateion Hosp, Dept Otolaryngol 1, Athens 11527, Greece
[2] Univ Hosp Patras, Dept Otolaryngol, Patras 26504, Greece
[3] Med Sch Hannover, Dept Otolaryngol & Head & Neck Surg, D-30625 Hannover, Germany
[4] Univ Hosp Patras, Dept Surg, Patras 26504, Greece
关键词
otorhinolaryngology; deep learning; artificial intelligence; convolutional neural network; computer vision; imaging; DIAGNOSTIC-ACCURACY; AUTOMATED DIAGNOSIS; ORAL DYSPLASIA; HEAD; NETWORK; IMAGES; CT; CLASSIFICATION; SEGMENTATION; PREDICTION;
D O I
10.3390/jcm12226973
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Over the last decades, the field of medicine has witnessed significant progress in artificial intelligence (AI), the Internet of Medical Things (IoMT), and deep learning (DL) systems. Otorhinolaryngology, and imaging in its various subspecialties, has not remained untouched by this transformative trend. As the medical landscape evolves, the integration of these technologies becomes imperative in augmenting patient care, fostering innovation, and actively participating in the ever-evolving synergy between computer vision techniques in otorhinolaryngology and AI. To that end, we conducted a thorough search on MEDLINE for papers published until June 2023, utilizing the keywords 'otorhinolaryngology', 'imaging', 'computer vision', 'artificial intelligence', and 'deep learning', and at the same time conducted manual searching in the references section of the articles included in our manuscript. Our search culminated in the retrieval of 121 related articles, which were subsequently subdivided into the following categories: imaging in head and neck, otology, and rhinology. Our objective is to provide a comprehensive introduction to this burgeoning field, tailored for both experienced specialists and aspiring residents in the domain of deep learning algorithms in imaging techniques in otorhinolaryngology.
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页数:16
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