ReviewJournal of imaging informatics in medicine2025
FireVoxel: Interactive Software for Multi-Modality Analysis of Dynamic Medical Images.
Review in Journal of imaging informatics in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed.
- Preoperative prediction of microsatellite instability in gastric cancer using quantitative multiparametric MRI with DCE-MRI and DWI.Abdominal radiology (New York) · 2026Article
- Recent advances and current landscape of software tools for image analysis and dosimetry in nuclear medicine.EJNMMI physics · 2026Review
- Evaluating Breast Cancer Intravoxel Incoherent Motion MRI Biomarkers across Software Platforms.Radiology. Imaging cancer · 2025Article
- Preoperative prediction of lymph node metastasis in pancreatic ductal adenocarcinoma using MRI-derived whole-tumor ADC histogram analysis.Frontiers in medicine · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
This article provides an overview of the FireVoxel software for quantitative analysis of medical images and its applications in the field. We describe FireVoxel's user interface, multi-layer design, dynamic parametric models, and several turn-key workflows. Additionally, we discuss its application in recent imaging projects. We outline basic image analysis tools such as segmentation, non-uniformity correction, and coregistration through a pictorial overview, with a focus on deformable coregistration and motion correction. Several example workflows and image-based dynamic modeling are also highlighted. Furthermore, we analyze peer-reviewed studies that utilized FireVoxel for image processing, categorizing published papers based on body structures/organs, image processing methods, and imaging modalities. For comparison, we searched the Ovid MEDLINE database to assess the general use of medical image analysis software. FireVoxel is used by over 3000 users worldwide, with 528 articles, including 413 in English, published in the past 15 years. MRI is the most commonly used imaging modality (78.2%), followed by CT (14.5%) and PET (7.3%). The most frequently used methods are dynamic modeling, segmentation, texture analysis, and coregistration. FireVoxel is commonly used in abdominal and genitourinary imaging studies, where it appears to fill a niche due to the lack of alternative software. The search of the Ovid MEDLINE suggests that quantitative medical imaging studies, on the other hand, focus on the brain and cardiovascular system. FireVoxel offers an effective set of quantitative tools, particularly for abdominal and genitourinary imaging, likely due to its ability to manage patient motion and correct for MR artifacts. The software is especially valuable for processing dynamic studies. The steady increase in publications utilizing FireVoxel reflects growing interest in this software and its relevance for image-based research.
Indexed as
Identifiers
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.