Support of deep learning to classify vocal fold images in flexible laryngoscopy.

Purpose: To collect a dataset with adequate laryngoscopy images and identify the appearance of vocal folds and their lesions in flexible laryngoscopy images by objective deep learning models.

Methods: We adopted a number of novel deep learning models to train and classify 4549 flexible laryngoscopy images as no vocal fold, normal vocal folds, and abnormal vocal folds. This could help these models recognize vocal folds and their lesions within these images.

Reconstruction of Large Anterior Skull Base Defects After Resection of Sinonasal Tumors With Intracranial Extension by Using Pedicled Double Flap Techniques.

Introduction: The use of surgical resection for large anterior skull base (ASB) tumors and sinonasal malignancies with intracranial extension will result in a large skull base defect. Reconstruction of large ASB defects using traditional techniques is high risk and may lead to postoperative cerebral spinal fluid (CSF) leakage, meningitis, and an increase in mortality rate. The use of a pedicled double flap technique to reconstruct the ASB defect may decrease complications.

Combined Nasal Endoscopic and Subfrontal Craniotomy for Resection Tumors of Anterior Skull Base.

Objective: Sinonasal tumors invading anterior skull base is difficult to treat in Otorhinolaryngology and Neurosurgery. Treatment requires the collaboration of ear, nose and throat (ENT) and neurosurgeon to remove the tumor completely. This study was to evaluate the outcome of combined technique nasal endoscopic and subfrontal approach in case of sinonasal tumors involving anterior skull base.