98%
921
2 minutes
20
Objectives: The objectives of this study were to quantify the impact of image post-processing parameters on the apparent renal stone size, and to quantify the intra- and inter-reader variability in renal stone size estimation.
Methods: Fifty CT datasets including a renal or ureteral stone were included retrospectively during a prospective inclusion period. Each of the CT datasets was post-processed in different ways regarding slice thickness, slice increment and window setting. In the first part of the study a single reader repeated size estimations for the renal stones using different post-processing parameters. In the intra-reader variability experiment one reader reported size estimations for the same images with a one-week interval. The inter-reader variability data were obtained from 11 readers reporting size estimations for the same renal stones.
Results: The apparent stone size differed according to image post-processing parameters with the largest mean differences seen with regard to the window settings experiment (1.5 mm, p < 0.001) and slice thickness (0.8 mm, p < 0.001). Changes in parameters introduced a bias and a pseudo-random variability. The inter-reader variability was considerably larger than the intra-reader variability.
Conclusion: Our results indicate a need for the standardisation of making measurements on CT images.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1007/s00330-011-2171-x | DOI Listing |
Neuroradiology
September 2025
Universitair Ziekenhuis Leuven, Leuven, Belgium.
Aim: Volumetric analysis of orbital soft tissues using magnetic resonance imaging (MRI) offers valuable diagnostic and pathophysiological insights into orbital inflammation, trauma, and tumors. However, the optimal MRI protocols and post-processing methods for specific conditions remain unclear.
Methods: A systematic search was performed in PubMed/MEDLINE, Web of Science, and Cochrane Library for all studies published before November 2024.
Micromachines (Basel)
August 2025
School of Mechanical, Materials, Mechatronic and Biomedical Engineering, University of Wollongong, Wollongong, NSW 2522, Australia.
Stainless steel is essential in high-performance industries due to its strength, corrosion resistance, and biocompatibility. However, conventional manufacturing methods limit material efficiency, design complexity, and customization. Additive manufacturing (AM) has emerged as a powerful alternative, enabling the production of stainless-steel components with complex geometries, tailored microstructures, and integrated functionalities.
View Article and Find Full Text PDFEntropy (Basel)
August 2025
National Quantum Communication (Guangdong) Co., Ltd., Guangzhou 510700, China.
As a core component in quantum cryptography, Quantum Random Number Generators (QRNGs) face dual critical challenges: insufficient randomness enhancement and limited compatibility with post-processing algorithms. This study proposes an Adaptive Feedback Compensation Algorithm (AFCA) to address these limitations through dynamic parameter feedback and selective encryption strategies. The AFCA dynamically adjusts nonlinear transformation intensity based on real-time statistical deviations, retaining over 50% of original bits while correcting local imbalances.
View Article and Find Full Text PDFJ Clin Med
August 2025
Division of Cardiac Surgery, Department of Surgical Sciences, University of Turin, 10126 Turin, Italy.
: The NeoChord procedure is a trans-ventricular, echo-guided, beating-heart mitral valve (MV) repair technique used to treat degenerative mitral regurgitation (MR) caused by leaflet prolapse and/or flail. : This study aimed to develop a machine learning (ML) scoring system using pre-procedural clinical and echocardiographic variables to predict the success of the NeoChord procedure-defined as less than moderate MR at follow-up. A total of 80 patients were included.
View Article and Find Full Text PDFBrain Sci
July 2025
Institute of Neuroradiology, University Hospital Erlangen, Friedrich-Alexander-University Erlangen-Nürnberg, 91054 Erlangen, Germany.
Objective: This study aimed to evaluate whether modifying the post-processing algorithm of Twin-Spiral Dual-Energy computed tomography (DECT) improves infarct detection compared to conventional Dual-Energy CT (DECT) and Single-Energy CT (SECT) following endovascular therapy (EVT) for large vessel occlusion (LVO).
Methods: We retrospectively analyzed 52 patients who underwent Twin-Spiral DECT after endovascular stroke therapy. Ten patients were used to generate a device-specific parameter ("y") using an AI-based neural network (SynthSR).