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Maxillary Sinus

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Adaptive Localizing Region-Based Level Set for Segmentation of Maxillary Sinus Based on Convolutional Neural Networks.

Computational intelligence and neuroscience
In this paper, we propose a novel method, an adaptive localizing region-based level set using convolutional neural network, for improving performance of maxillary sinus segmentation. The healthy sinus without lesion inside is easy for conventional al...

Development and validation of a two-segment continuum robot for maxillary sinus surgery.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: Existing rigid instruments have difficulties in backward inspection and operation. Moreover, the pathway to the maxillary sinus is curved and narrow, resulting in complex and repetitive manual operations. There is a necessity to develop a...

Detection of maxillary sinus fungal ball via 3-D CNN-based artificial intelligence: Fully automated system and clinical validation.

PloS one
BACKGROUND: This study aims to develop artificial intelligence (AI) system to automatically classify patients with maxillary sinus fungal ball (MFB), chronic rhinosinusitis (CRS), and healthy controls (HCs).

Automatic detection and segmentation of morphological changes of the maxillary sinus mucosa on cone-beam computed tomography images using a three-dimensional convolutional neural network.

Clinical oral investigations
OBJECTIVES: To propose and evaluate a convolutional neural network (CNN) algorithm for automatic detection and segmentation of mucosal thickening (MT) and mucosal retention cysts (MRCs) in the maxillary sinus on low-dose and full-dose cone-beam compu...

A miniature robotic steerable endoscope for maxillary sinus surgery called PliENT.

Scientific reports
In endoscopic maxillary sinus surgery, the maxillary sinus is accessed through the nasal cavity which constitutes a narrow and tortuous pathway. However, surgeons still use rigid endoscopes and rigid, straight or pre-bent instruments for this procedu...

Semi-Supervised Deep Learning Semantic Segmentation for 3D Volumetric Computed Tomographic Scoring of Chronic Rhinosinusitis: Clinical Correlations and Comparison with Lund-Mackay Scoring.

Tomography (Ann Arbor, Mich.)
BACKGROUND: The traditional Lund-Mackay score (TLMs) is unable to subgrade the volume of inflammatory disease. We aimed to propose an effective modification and calculated the volume-based modified LM score (VMLMs), which should correlate more strong...

Convolutional neural network for automatic maxillary sinus segmentation on cone-beam computed tomographic images.

Scientific reports
An accurate three-dimensional (3D) segmentation of the maxillary sinus is crucial for multiple diagnostic and treatment applications. Yet, it is challenging and time-consuming when manually performed on a cone-beam computed tomography (CBCT) dataset....

Deep learning-based fully automatic segmentation of the maxillary sinus on cone-beam computed tomographic images.

Scientific reports
The detection of maxillary sinus wall is important in dental fields such as implant surgery, tooth extraction, and odontogenic disease diagnosis. The accurate segmentation of the maxillary sinus is required as a cornerstone for diagnosis and treatmen...

Design and path tracking control of a continuum robot for maxillary sinus surgery.

International journal of computer assisted radiology and surgery
PURPOSE: Continuum robots (CRs) have been developed for maxillary sinus surgery (MSS) in recent years. However, due to the anatomically curved and narrow pathway of the maxillary sinus and the deformable characteristics of the CR, it is still a chall...

Multiple instance ensembling for paranasal anomaly classification in the maxillary sinus.

International journal of computer assisted radiology and surgery
PURPOSE: Paranasal anomalies are commonly discovered during routine radiological screenings and can present with a wide range of morphological features. This diversity can make it difficult for convolutional neural networks (CNNs) to accurately class...