Abstract
Flexible endoscopy was used in examination cervix lesion the first was studied by Nishiyama et al was reported the used of endoscopy for diagnosing cervical neoplasms. The second study of K Uchita et al.
Highlights
A cohort of high-speed videoendoscopies was evaluated for usability for deep learning
The interesting result is that oblique angle pictures (10%) as well as insufficient pictures of the front of the vocal folds and arytenoids (14%) were the largest groups of the non-usable
The aim of our study was to find the percentage of our clinical material of 15.732 highspeed videos that could be used for deep learning (AI) and later Optical Coherence Tomography (OCT)
Summary
A cohort of high-speed videoendoscopies was evaluated for usability for deep learning. The aim of our study was to find the percentage of our high-speed videos (15.732) that could be used for deep learning (AI). A screening of the material showed that some videos had artefacts, making them non usable for deep learning. We were interested in a co-operation for deep learning since we wanted our prospective cohort of high-speed video endoscopy results to be analysed [1]. High-speed video is usable to quantify vocal fold measurements [2-9]. Videos can be affected by patient movement, as well as with nonlinear distortions and phase asymmetry [14,15] Artifacts, such as parts of the glottis concealed, and parts of the arytenoid cartilage can cover other parts.
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