ArticleJournal of medical systems2018
Advantages and Disadvantages in Image Processing with Free Software in Radiology.
Article in Journal of medical systems, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed.
- No difference in mobile and fixed bearing partial knee arthroplasty in octogenarians: a clinical trial.European journal of orthopaedic surgery & traumatology : orthopedie traumatologie · 2023Trial
- Beyond the surface: A review of current and potential micro-CT applications in paleopathology.International journal of paleopathology · 2026Review
- FNDC5/irisin mediates the protective effects of Innovative theta-shaking exercise on mouse memory.Heliyon · 2024Article
- Learning curve of Persona Partial Knee (PPK) arthroplasty: a clinical trial.BMC musculoskeletal disorders · 2024Article
- Similar clinical and radiographic outcomes after two different hypoallergenic medial unicompartmental knee in patients with metal allergy.European journal of orthopaedic surgery & traumatology : orthopedie traumatologie · 2023Article
- Letter to the editor: is total psoas muscle area at L3 truly representative of its volume?The British journal of radiology · 2022Article
- Similar rates of return to sports and BMI reduction regardless of age, gender and preoperative BMI as seen in matched cohort of hypoallergenic and standard Cobalt Chromium medial unicompartmental knee arthroplasty.Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA · 2022Article
- Nontargeted metabolomics-based multiple machine learning modeling boosts early accurate detection for citrus Huanglongbing.Horticulture research · 2022Article
- No Clinical or Radiographic Differences Between Cemented Cobalt-Chromium and Titanium-Niobium Nitride Mobile-Bearing Unicompartmental Knee Arthroplasty.Indian journal of orthopaedics · 2021Article
- Review of the main surgical and angiographic-oriented classifications of the course of the internal carotid artery through a novel interactive 3D model.Neurosurgical review · 2020Review
- Machine Learning Techniques for Soybean Charcoal Rot Disease Prediction.Frontiers in plant science · 2020Article
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
Currently, there are sophisticated applications that make it possible to visualize medical images and even to manipulate them. These software applications are of great interest, both from a teaching and a radiological perspective. In addition, some of these applications are known as Free Open Source Software because they are free and the source code is freely available, and therefore it can be easily obtained even on personal computers. Two examples of free open source software are Osirix Lite® and 3D Slicer®. However, this last group of free applications have limitations in its use. For the radiological field, manipulating and post-processing images is increasingly important. Consequently, sophisticated computing tools that combine software and hardware to process medical images are needed. In radiology, graphic workstations allow their users to process, review, analyse, communicate and exchange multidimensional digital images acquired with different image-capturing radiological devices. These radiological devices are basically CT (Computerised Tomography), MRI (Magnetic Resonance Imaging), PET (Positron Emission Tomography), etc. Nevertheless, the programs included in these workstations have a high cost which always depends on the software provider and is always subject to its norms and requirements. With this study, we aim to present the advantages and disadvantages of these radiological image visualization systems in the advanced management of radiological studies. We will compare the features of the VITREA2® and AW VolumeShare 5® radiology workstation with free open source software applications like OsiriX® and 3D Slicer®, with examples from specific studies.
Indexed as
Identifiers
29333590What 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.