Objectives This study proposed and investigated the performance of a deep learning based
three-dimensional (3D) convolutional neural network (CNN) model for automatic …

Rationale and Objectives Accurate segmentation of the upper airway lumen and
surrounding soft tissue anatomy, especially tongue fat, using magnetic resonance images is …

Purpose Upper airway segmentation on MR images is a prerequisite step for quantitatively
studying the anatomical structure and function of the upper airway and surrounding tissues …

Purpose The main purpose of this work was to develop an efficient approach for
segmentation of structures that are relevant for diagnosis and treatment of obstructive sleep …

Background Obstructive sleep apnea (OSA) is a public health problem. Detailed analysis of
the para-pharyngeal fat pads can help us to understand the pathogenesis of OSA and may …

Background: Obstructive sleep apnea (OSA) is a chronic sleeping disorder. The analysis of
the pharynx and its surrounding tissues can play a vital role in understanding the …

Classification of image regions is a crucial step in many image segmentation algorithms.
Assigning a segment to a certain class can be based on various numerical characteristics …

Obstructive sleep apnea (OSA) is a public health problem. Volumetric analysis of the upper
airways can help us to understand the pathogenesis of OSA. A reliable pharynx …

A new algorithm for 3D throat region segmentation from magnetic resonance imaging (MRI)
is presented. The proposed algorithm initially pre-processes the MRI data to increase the …

The main purpose of our project was to automatically delineate parapharyngeal fat pads
from magnetic resonance imaging (MR) data, since these structures are considered …