ArticleIEEE transactions on visualization and computer graphics2022
3D Virtual Pancreatography.
Article in IEEE transactions on visualization and computer graphics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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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.
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Who cites it
6 citing papers in PubMed.
- 3D Modelling for Preoperative Planning, Intraoperative Navigation, and Training in Pancreatic Surgery: A Systematic Review.Annals of surgery open : perspectives of surgical history, education, and clinical approaches · 2026Review
- 3D IntelliGenes: AI/ML application using multi-omics data for biomarker discovery and disease prediction with multi-dimensional visualization.BMC medical research methodology · 2025Article
- Artificial intelligence in pancreatic intraductal papillary mucinous neoplasm imaging: A systematic review.PLOS digital health · 2025Article
- Centerline-guided reinforcement learning model for pancreatic duct identifications.Journal of medical imaging (Bellingham, Wash.) · 2024Article
- COVID-view: Diagnosis of COVID-19 using Chest CT.IEEE transactions on visualization and computer graphics · 2022Article
- Artificial intelligence in pancreatic cancer.Theranostics · 2022Review
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
We present 3D virtual pancreatography (VP), a novel visualization procedure and application for non-invasive diagnosis and classification of pancreatic lesions, the precursors of pancreatic cancer. Currently, non-invasive screening of patients is performed through visual inspection of 2D axis-aligned CT images, though the relevant features are often not clearly visible nor automatically detected. VP is an end-to-end visual diagnosis system that includes: A machine learning based automatic segmentation of the pancreatic gland and the lesions, a semi-automatic approach to extract the primary pancreatic duct, a machine learning based automatic classification of lesions into four prominent types, and specialized 3D and 2D exploratory visualizations of the pancreas, lesions and surrounding anatomy. We combine volume rendering with pancreas- and lesion-centric visualizations and measurements for effective diagnosis. We designed VP through close collaboration and feedback from expert radiologists, and evaluated it on multiple real-world CT datasets with various pancreatic lesions and case studies examined by the expert radiologists.
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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.