ReviewIEEE transactions on medical imaging2018
Application of the 4-D XCAT Phantoms in Biomedical Imaging and Beyond.
Review in IEEE transactions on medical imaging, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 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
45 citing papers in PubMed.
- Segmentation-based deep learning emphysema quantification using chest CT: improved accuracy and robustness vs LAA-950.European radiology · 2026Article
- Clinically relevant effective dose k-factors for brain CT derived from Korean body size phantoms and National CT Dose Index Registry Data.Radiological physics and technology · 2026Article
- Ideal observer estimation for binary tasks with stochastic object models.Physics in medicine and biology · 2026Article
- Virtual Imaging-Guided Harmonization of Chest X-rays Using a Generative Adversarial Neural Network.IEEE transactions on bio-medical engineering · 2026Article
- Modality-agnostic, patient-specific digital twins modeling temporally varying digestive motion.Physics in medicine and biology · 2026Article
- Generative AI and foundation models in medical image.Radiological physics and technology · 2025Review
- Investigation of Attenuation Correction Methods for Dual-Gated Single Photon Emission Computed Tomography (DG-SPECT).Bioengineering (Basel, Switzerland) · 2025Article
- An end-to-end CT simulation framework with graphical user interface and sample scanner models.Medical physics · 2025Article
- Effects of Intra-patient Lung Volume Variability on CT-Based Emphysema Quantification: A Virtual Imaging Study.Academic radiology · 2025Article
- XCAT 3.0: A comprehensive library of personalized digital twins derived from CT scans.Medical image analysis · 2025Article
- Toward widespread use of virtual trials in medical imaging innovation and regulatory science.Medical physics · 2024Review
- Monte Carlo methods for medical imaging research.Biomedical engineering letters · 2024Review
- Evaluating the accuracy of planar gated blood pool processing software using simulated patient studies.Heliyon · 2024Article
- Deep learning applications for quantitative and qualitative PET in PET/MR: technical and clinical unmet needs.Magma (New York, N.Y.) · 2024Review
- A systematic assessment and optimization of photon-counting CT for lung density quantifications.Medical physics · 2024Article
- Synthetic data in radiological imaging: current state and future outlook.BJR artificial intelligence · 2024Review
- In silico simulation of hepatic arteries: An open-source algorithm for efficient synthetic data generation.Medical physics · 2023Article
- Simulation of a new respiratory phase sorting method for 4D-imaging using optical surface information towards precision radiotherapy.Computers in biology and medicine · 2023Article
- Article
- Attenuation Correction for Dedicated Cardiac SPECT Imaging Without Using Transmission Data.Molecular imaging and radionuclide therapy · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
The four-dimensional (4-D) eXtended CArdiac-Torso (XCAT) series of phantoms was developed to provide accurate computerized models of the human anatomy and physiology. The XCAT series encompasses a vast population of phantoms of varying ages from newborn to adult, each including parameterized models for the cardiac and respiratory motions. With great flexibility in the XCAT's design, any number of body sizes, different anatomies, cardiac or respiratory motions or patterns, patient positions and orientations, and spatial resolutions can be simulated. As such, the XCAT phantoms are gaining a wide use in biomedical imaging research. There they can provide a virtual patient base from which to quantitatively evaluate and improve imaging instrumentation, data acquisition, techniques, and image reconstruction and processing methods which can lead to improved image quality and more accurate clinical diagnoses. The phantoms have also found great use in radiation dosimetry, radiation therapy, medical device design, and even the security and defense industry. This review paper highlights some specific areas in which the XCAT phantoms have found use within biomedical imaging and other fields. From these examples, we illustrate the increasingly important role that computerized phantoms and computer simulation are playing in the research community.
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What Socratic 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 Socratic graph.