On Efficient Segmentation of Parapharyngeal Fat Pads From Population-based MRIs: An Obstructive Sleep Apnea Application

Tatyana Ivanovska,Amro Daboul,Oleksandr Kalentev,Norbert Hosten,Henry Völzke,Reiner Biffar,Florentin Wörgötter

2021 6th International Conference on Communication, Image and Signal Processing (CCISP)（2021）

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Abstract

The main purpose of our project was to automatically delineate parapharyngeal fat pads from magnetic resonance imaging (MR) data, since these structures are considered important for diagnosis of obstructive sleep apnea syndrome (OSAS). Here, we investigate the problem, discuss possible data choices, compare 2D and 3D networks, and consider several automated processing steps. First, approximately 7...

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Key words

Training,Image segmentation,Three-dimensional displays,Magnetic resonance imaging,Observers,Signal processing,Sleep apnea

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