ArticleScientific data2019
Facial model collection for medical augmented reality in oncologic cranio-maxillofacial surgery.
Article in Scientific data, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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
7 citing papers in PubMed.
- Comprehensive protocol for mixed reality visualization and navigation using 3D Slicer.PloS one · 2026Article
- Article
- Type B Aortic Dissection CTA Collection with True and False Lumen Expert Annotations for the Development of AI-based Algorithms.Scientific data · 2024Article
- Head model dataset for mixed reality navigation in neurosurgical interventions for intracranial lesions.Scientific data · 2024Article
- Treatment Planning Strategies for Interstitial Ultrasound Ablation of Prostate Cancer.IEEE open journal of engineering in medicine and biology · 2024Article
- Smartphone Photogrammetric Assessment for Head Measurements.Sensors (Basel, Switzerland) · 2023Article
- Facial model collection for medical augmented reality in oncologic cranio-maxillofacial surgery.Scientific data · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Medical augmented reality (AR) is an increasingly important topic in many medical fields. AR enables x-ray vision to see through real world objects. In medicine, this offers pre-, intra- or post-interventional visualization of "hidden" structures. In contrast to a classical monitor view, AR applications provide visualization not only on but also in relation to the patient. However, research and development of medical AR applications is challenging, because of unique patient-specific anatomies and pathologies. Working with several patients during the development for weeks or even months is not feasible. One alternative are commercial patient phantoms, which are very expensive. Hence, this data set provides a unique collection of head and neck cancer patient PET-CT scans with corresponding 3D models, provided as stereolitography (STL) files. The 3D models are optimized for effective 3D printing at low cost. This data can be used in the development and evaluation of AR applications for head and neck surgery.
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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.