ReviewThe neuroradiology journal2021
Segmentation procedures for the assessment of paranasal sinuses volumes.
Review in The neuroradiology journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Comparisons of artificial intelligence automated segmentation techniques to manual segmentation techniques of the maxilla and maxillary sinus for CT or cone-beam CT scans-a systematic review.Dento maxillo facial radiology · 2025Pooled it
- Morphometric Analysis of the Maxillary Sinus Using CT-Based Air-Cavity Reconstruction: A Retrospective Study.Journal of clinical medicine · 2026Article
- Morphological and Epidemiological Analysis of the Sphenoid Sinus Based on Computed Tomography and Magnetic Resonance Imaging: A Narrative Review.Life (Basel, Switzerland) · 2026Review
- Development of an AI-based model for sex estimation using CT-derived metrics from paranasal sinuses.International journal of legal medicine · 2026Observational
- Comparison of Two Methods for Assessing the Maxillary Sinus Volume in Patients with and Without Unilateral Cleft Lip and Palate: A Retrospective Cross-Sectional Study.Diagnostics (Basel, Switzerland) · 2026Article
- Development of an Open-Source Algorithm for Automated Segmentation in Clinician-Led Paranasal Sinus Radiologic Research.The Laryngoscope · 2025Article
- Retrospective Evaluation of Maxillary Sinus Volume Changes Following Bone-Anchored Midface Distraction Osteogenesis in Cleft Patients: A Case-Series Study.Journal of clinical medicine · 2025Article
- CT-SCOPE: annotated dataset of CT SCans for the automatic semantic segmentation of the Osseous structures of the Paranasal sinusEs.Data in brief · 2025Article
- Human identification: an investigation of 3D models of paranasal sinuses to establish a biological profile on a modern UK population.International journal of legal medicine · 2024Article
- Article
- Three-dimensional evaluation of maxillary sinus volume, skeletal and dentoalveolar maxillary anterior region, in unilateral palatally impacted maxillary canine (Cross-sectional study).Journal of orthodontic science · 2023Article
- Convolutional neural network for automatic maxillary sinus segmentation on cone-beam computed tomographic images.Scientific reports · 2022Article
- Volumetric growth analysis of maxillary sinus using computed tomography scan segmentation: a pilot study of Indonesian population.Anatomy & cell biology · 2021Article
- MIScnn: a framework for medical image segmentation with convolutional neural networks and deep learning.BMC medical imaging · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe paranasal sinuses are complex anatomical structures, characterised by highly variable shape, morphology and size. With the introduction of multidetector scanners and the development of many post-processing possibilities, computed tomography became the gold standard technique to image the paranasal sinuses. Segmentation allows the extraction of metrical and shape data of these anatomical components that can be applied for diagnostic, education, surgical planning and simulation, and to plan minimally invasive interventions in otorhinolaryngology and neurosurgery. DISCUSSION: Our aim was to provide a review of the existing literature on segmentation, its types and application, and the data obtained from this procedure. The literature search was conducted on PubMed (including Medline), ScienceDirect and Google Scholar databases, using the keywords as follows: 'paranasal sinuses', 'frontal sinus', 'maxillary sinus', 'sphenoid sinus', 'ethmoid sinus', in all possible combinations with the keywords 'segmentation' and 'volumetric analysis'. Inclusion criteria were: articles written in English, on living human subjects, on the adult population and focused on paranasal sinuses analysis.
conclusionThis article provides an overview of the types and main application of segmentation procedures on paranasal sinuses, and the results provided by the studies on this topic.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.