Classification of Different Tympanic Membrane Conditions Using Fused Deep Hypercolumn Features and Bidirectional LSTM
Yazarlar (4)
M. Uçar Iskenderun Technical University, Türkiye
Prof. Dr. Kemal AKYOL Kastamonu Üniversitesi, Türkiye
Atila Karabük Üniversitesi, Türkiye
E. Uçar Iskenderun Technical University, Türkiye
| Makale Türü | Özgün Makale (SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale) | ||
| Dergi Adı | Irbm (Q2) | ||
| Dergi ISSN | 1959-0318 Wos Dergi Scopus Dergi | ||
| Dergi Tarandığı Indeksler | SCI-Expanded | ||
| Makale Dili | İngilizce | Basım Tarihi | 06-2022 |
| Kabul Tarihi | – | Yayınlanma Tarihi | 01-06-2022 |
| Cilt / Sayı / Sayfa | 43 / 3 / 187–197 | DOI | 10.1016/j.irbm.2021.01.001 |
| Makale Linki | 10.1016/j.irbm.2021.01.001 | ||
| Özet |
| Objectives: Middle ear inflammatory diseases are global health problem that can have serious consequences such as hearing loss and speech disorders. The high cost of medical devices such as oto-endoscope and oto-microscope used by the specialists for the diagnosis of the disease prevents its widespread use. In addition, the decisions of otolaryngologists may differ due to the subjective visual examinations. For this reason, computer-aided middle ear disease diagnosis systems are needed to eliminate subjective diagnosis and high cost problems. To this aim, a hybrid deep learning approach was proposed for automatic recognition of different tympanic membrane conditions such as earwax plug, myringosclerosis, chronic otitis media and normal from the otoscopy images.Materials and methods: In this study we used public Ear Imagery dataset containing 880 otoscopy images. The proposed approach detects … |
| Anahtar Kelimeler |
| Bidirectional LSTM | Deep learning | Hypercolumn features | Keypoint detection | Tympanic membrane |
Science Direct
Classification of Different Tympanic Membrane Conditions Using Fused Deep Hypercolumn Features and Bidirectional LSTM
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Scopus | 10 |
| Google Scholar | 16 |