AIMC Topic: Turbinates

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Deep learning-based allergic rhinitis diagnosis using nasal endoscopy images.

Scientific reports Jul 8, 2025
Allergic rhinitis typically has edematous and pale turbinates or erythematous and inflamed turbinates. While traditional approaches include using skin prick tests (SPT) to determine the presence of AR, It is often not related to actual symptoms, and ...
Humans Female Adult Endoscopy Male Middle Aged Deep Learning Image Processing, Computer-Assisted Rhinitis, Allergic Turbinates
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A Label-Efficient Framework for Automated Sinonasal CT Segmentation in Image-Guided Surgery.

Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery Jun 23, 2024
OBJECTIVE: Segmentation, the partitioning of patient imaging into multiple, labeled segments, has several potential clinical benefits but when performed manually is tedious and resource intensive. Automated deep learning (DL)-based segmentation metho...
Humans Retrospective Studies Tomography, X-Ray Computed Male Deep Learning Surgery, Computer-Assisted Paranasal Sinuses Maxillary Sinus Turbinates Nasal Septum
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Enhancing nasal endoscopy: Classification, detection, and segmentation of anatomic landmarks using a convolutional neural network.

International forum of allergy & rhinology Jun 10, 2024
A convolutional neural network (CNN)-based model can accurately localize and segment turbinates in images obtained during nasal endoscopy (NE). This model represents a starting point for algorithms that comprehensively interpret NE findings.
Humans Neural Networks, Computer Algorithms Endoscopy Anatomic Landmarks Nose Turbinates
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An artificial intelligence algorithm that identifies middle turbinate pneumatisation (concha bullosa) on sinus computed tomography scans.

The Journal of laryngology and otology Apr 1, 2020
OBJECTIVE: Convolutional neural networks are a subclass of deep learning or artificial intelligence that are predominantly used for image analysis and classification. This proof-of-concept study attempts to train a convolutional neural network algori...
Humans Neural Networks, Computer Artificial Intelligence Algorithms Retrospective Studies Tomography, X-Ray Computed Female Male Australia Paranasal Sinuses Observer Variation Nose Diseases Turbinates
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