Nasal endoscopy (NAE) is an important diagnostic tool, but the complex structure of the nasal cavity can make it difficult to use. Researchers have created a model based on convolutional neural networks (CNNs) to recognize and highlight important structures in endoscopy images.
The model was trained on 2,111 endoscopy images performed at Ochsner Medical Center from 2014 to 2023. The developed system achieved 91.5% accuracy in recognizing the inferior and middle turbinates.
This technology may be particularly useful for novice and non-specialist physicians who have difficulty with the complex anatomy of the nasal cavity.
Source: Ferra
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