AIMC Topic: Ear, Middle
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Deep learning multi-classification of middle ear diseases using synthetic tympanic images.
Acta oto-laryngologica
Jan 10, 2025
BACKGROUND: Recent advances in artificial intelligence have facilitated the automatic diagnosis of middle ear diseases using endoscopic tympanic membrane imaging.
Deep Learning for Automated Image Segmentation of the Middle Ear: A Scoping Review.
Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery
Apr 26, 2024
OBJECTIVE: Convolutional neural networks (CNNs) have revolutionized medical image segmentation in recent years. This scoping review aimed to carry out a comprehensive review of the literature describing automated image segmentation of the middle ear ...
Improving image quality of the middle ear with ultra-high-resolution CT coupled with deep-learning image reconstruction algorithm.
Diagnostic and interventional imaging
Feb 23, 2024
A Hybrid Deep Learning Approach to Identify Preventable Childhood Hearing Loss.
Ear and hearing
Jun 15, 2023
OBJECTIVE: Childhood hearing loss has well-known, lifelong consequences. Infection-related hearing loss disproportionately affects underserved communities yet can be prevented with early identification and treatment. This study evaluates the utility ...
The effect of soft palate reconstruction with the da Vinci robot on middle ear function in children: an observational study.
International journal of oral and maxillofacial surgery
Mar 11, 2023
Cleft palate is associated with a high prevalence of middle ear dysfunction, even after palatal repair. The aim of this study was to evaluate the effects of robot-enhanced soft palate closure on middle ear functioning. This retrospective study compar...
A deep learning approach to the diagnosis of atelectasis and attic retraction pocket in otitis media with effusion using otoscopic images.
European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
Oct 13, 2022
BACKGROUND: This study aimed to develop and validate a deep learning (DL) model to identify atelectasis and attic retraction pocket in cases of otitis media with effusion (OME) using multi-center otoscopic images.
Geometric Atlas of the Middle Ear and Paranasal Sinuses for Robotic Applications.
Surgical innovation
Oct 3, 2021
In otolaryngologic surgery, more and more robots are being studied to meet the clinical needs of operating rooms. However, to help design and optimize these robots, the workspace must be precisely defined taking into account patient variability. The ...
Shortwave infrared otoscopy for diagnosis of middle ear effusions: a machine-learning-based approach.
Scientific reports
Jun 15, 2021
Otitis media, a common disease marked by the presence of fluid within the middle ear space, imparts a significant global health and economic burden. Identifying an effusion through the tympanic membrane is critical to diagnostic success but remains c...
Application of artificial intelligence using a convolutional neural network for detecting cholesteatoma in endoscopic enhanced images.
Auris, nasus, larynx
Apr 4, 2021
OBJECTIVE: We examined whether artificial intelligence (AI) used with the novel digital image enhancement system modalities (CLARA+CHROMA, SPECTRA A, and SPECTRA B) could distinguish the cholesteatoma matrix, cholesteatoma debris, and normal middle e...
Ear-Bot: Locust Ear-on-a-Chip Bio-Hybrid Platform.
Sensors (Basel, Switzerland)
Jan 1, 2021
During hundreds of millions of years of evolution, insects have evolved some of the most efficient and robust sensing organs, often far more sensitive than their man-made equivalents. In this study, we demonstrate a hybrid bio-technological approach,...
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