ReviewVisual computing for industry, biomedicine, and art2023
Survey of methods and principles in three-dimensional reconstruction from two-dimensional medical images.
Review in Visual computing for industry, biomedicine, and art, 2023. 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.
- Semantic-guided 3D Gaussian splatting for sparse-view reconstruction in industrial digital twins.Visual computing for industry, biomedicine, and art · 2026Article
- DiGS: Depth-Initialized Gaussian Splatting for Single-Object Reconstruction.Journal of imaging · 2026Article
- Multimodal Guidewire 3D Reconstruction Based on Magnetic Field Data.Sensors (Basel, Switzerland) · 2026Article
- Body Cosmos 2.0: embodied biofeedback interface for dancing.Visual computing for industry, biomedicine, and art · 2025Article
- Survey of real-time brainmedia in artistic exploration.Visual computing for industry, biomedicine, and art · 2024Review
- IQAGPT: computed tomography image quality assessment with vision-language and ChatGPT models.Visual computing for industry, biomedicine, and art · 2024Article
- Dual modality prompt learning for visual question-grounded answering in robotic surgery.Visual computing for industry, biomedicine, and art · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Three-dimensional (3D) reconstruction of human organs has gained attention in recent years due to advances in the Internet and graphics processing units. In the coming years, most patient care will shift toward this new paradigm. However, development of fast and accurate 3D models from medical images or a set of medical scans remains a daunting task due to the number of pre-processing steps involved, most of which are dependent on human expertise. In this review, a survey of pre-processing steps was conducted, and reconstruction techniques for several organs in medical diagnosis were studied. Various methods and principles related to 3D reconstruction were highlighted. The usefulness of 3D reconstruction of organs in medical diagnosis was also highlighted.
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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.