ArticleJournal of Korean medical science2019
Real-Color Volume Models Made from Real-Color Sectioned Images of Visible Korean.
Article in Journal of Korean medical science, 2019. 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.
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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
14 citing papers in PubMed, 1 synthesis or guideline pooled it, 25 citations in OpenAlex.
- Gray Matter Volume Abnormality in Chronic Pain Patients With Depressive Symptoms: A Systemic Review and Meta-Analysis of Voxel-Based Morphometry Studies.Frontiers in neuroscience · 2022Pooled it
- Evaluation of glasses-free 3D anatomy learning materials through a randomized control study with a puzzle-like method.Anatomical sciences education · 2025Trial
- Revolutionizing Sectioned Images of the Visible Korean: Achieving From 0.05 mm to 0.03 mm Sized Pixel.Journal of Korean medical science · 2026Article
- Ophthalmic artery branches and adjacent nerves observed on sectioned images of cadaver.Anatomical science international · 2026Article
- Ultrasonographic images and correspondence with real color sectioned images of the upper limb.Surgical and radiologic anatomy : SRA · 2024Article
- Visible Korean based on true color sectioned images for making realistic digital human, twenty years' record: a review.Surgical and radiologic anatomy : SRA · 2024Review
- Lymph Node Stations of Pancreas Which Are Identified in Real Color Sectioned Images of a Cadaver With Pancreatic Cancer.Journal of Korean medical science · 2023Article
- A Novel Human Brainstem Map Based on True-Color Sectioned Images.Journal of Korean medical science · 2023Article
- Identification of cranial nerve ganglia using sectioned images and three-dimensional models of a cadaver.The Korean journal of pain · 2022Article
- Real color volume model of cadaver for learning cardiac computed tomographs and echocardiographs.Surgical and radiologic anatomy : SRA · 2021Article
- Peeled images and sectioned images from real-color volume models of foot.Surgical and radiologic anatomy : SRA · 2021Article
- Dawn of the Visible Monkey: Segmentation of the Rhesus Monkey for 2D and 3D Applications.Journal of Korean medical science · 2020Article
- Effects of Reading a Free Electronic Book on Regional Anatomy with Schematics and Mnemonics on Student Learning.Journal of Korean medical science · 2020Article
- Advanced Sectioned Images of a Cadaver Head with Voxel Size of 0.04 mm.Journal of Korean medical science · 2019Article
Corrections and comments
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Authors and funding
2 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundVolume models made from magnetic resonance images on computed tomographs can produce horizontal, coronal, sagittal, and oblique planes that are used widely in clinics, although detailed structures cannot be identified. Existing real color volume models are mostly commercial and their production methods have not been released. The aim of this study was to distribute free of charge, real-color volume models produced from sectioned images with the production method.
methodsThe original voxel size of sectioned images was increased appropriately so that the volume model could be handled by typical personal computers. By using Dicom Browser and MRIcroGL, the sectioned images were processed to become the volume models.
resultsOn the MRIcroGL, the resultant volume model with the voxel size of 0.5 × 0.5 × 0.5 mm
conclusionThe volume models can be used by medical students and doctors for learning sectional anatomy. Other researchers can utilize the method of this study to produce volume models from their own sectioned images.
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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.