Results 91 to 100 of about 38,801 (275)

OUCH: Oversampling and Undersampling Cannot Help Improve Accuracy in Our Bayesian Classifiers That Predict Preeclampsia

Mathematics
Unbalanced data can have an impact on the machine learning (ML) algorithms that build predictive models. This manuscript studies the influence of oversampling and undersampling strategies on the learning of the Bayesian classification models that predict
Franklin Parrales-Bravo, Rosangela Caicedo-Quiroz, Elena Tolozano-Benitez, Víctor Gómez-Rodríguez, Lorenzo Cevallos-Torres, Jorge Charco-Aguirre, Leonel Vasquez-Cevallos   +6 more
doaj   +1 more source

Deep‐Learning‐Based Image Reconstruction to Improve End‐Diastolic and Systolic Cardiac T1 Mapping

Magnetic Resonance in Medicine, EarlyView.
ABSTRACT Purpose To develop an image reconstruction method that enables increased spatial resolution cardiac T1 mapping in both the end‐diastolic and systolic phase, that shows high T1 agreement with the clinical standard. The resolution gain is achieved by increasing the acceleration rate of MOLLI single‐shot images to R = 4, while maintaining a ...
Daniel Amsel, Jens Wetzl, Daniel Giese, Christoph Tillmanns, Rolf Gebker, Kelvin Chow, Michaela Schmidt, Andreas Lingg, Jens Kübler, Patrick Krumm, Thomas Küstner   +10 more
wiley   +1 more source

Water/Fat Separated Echo Planar Time‐Resolved Imaging (WFS‐EPTI) for Distortion‐Free Multi‐Contrast MRI

Magnetic Resonance in Medicine, EarlyView.
ABSTRACT Purpose Echo‐planar time‐resolved imaging (EPTI) provides distortion‐ and T2/T2* blurring‐free multi‐echo/multi‐contrast imaging with fast speed, making it an efficient acquisition method for various MRI applications. Here, we aim to achieve water–fat separation for EPTI to improve fat signal removal for brain/body imaging applications. Theory
Zhangxuan Hu, Timothy G. Reese, Lawrence L. Wald, Jonathan R. Polimeni, Zijing Dong, Fuyixue Wang   +5 more
wiley   +1 more source

Deep Learning Reconstruction Enables Diagnostic-Quality 0.4T Knee and Spine MRI in One-Third of the Time. [PDF]

NMR Biomed
The deep learning model CIRIM successfully accelerated knee and spine data up to an acceleration factor of 3, after optimizing the undersampling mask and loss function. The model demonstrated robustness and generalizability to different contrasts, matrix sizes, orientations, and anatomies. ABSTRACT There has been a growing interest in low‐field MRI due
van den Berg DM, Varriale R, Ferrando F, Traverso P, Balbi L, Belgiorno G, Beekman K, Kox L, Strijkers GJ, Caan MWA.   +9 more
europepmc   +2 more sources

Dynamic Mode Decomposition (DMD) for Low‐Latency Real‐Time Cardiac MRI

Magnetic Resonance in Medicine, EarlyView.
ABSTRACT Purpose To demonstrate dynamic mode decomposition (DMD) for high spatiotemporal low‐latency online reconstruction in 2D real‐time cardiac MRI. Methods DMD was applied to 2D spiral balanced steady state free precession (bSSFP) real‐time adult and fetal cardiac MRI at 0.55 T, with data from 10 healthy adult volunteers (3F/7M; age: 21–49; BMI: 20–
Ecrin Yagiz, Bilal Tasdelen, Ibrahim K. Ozaslan, Mihailo R. Jovanovic, Ye Tian, Krishna S. Nayak   +5 more
wiley   +1 more source

The Influence of Radial Undersampling Schemes on Compressed Sensing in Cardiac DTI

Sensors, 2018
Diffusion tensor imaging (DTI) is known to suffer from long acquisition time, which greatly limits its practical and clinical use. Undersampling of k-space data provides an effective way to reduce the amount of data to acquire while maintaining image ...
Jianping Huang, Wenlong Song, Lihui Wang, Yuemin Zhu   +3 more
doaj   +1 more source

A Hybrid RF Coil for Whole‐Brain Imaging in Non‐Human Primates at 7 T

Magnetic Resonance in Medicine, EarlyView.
ABSTRACT Purpose Ultra‐high field MRI (≥ 7 T) offers unprecedented potential for mapping non‐human primate (NHP) brain function. However, complex electromagnetic systems are required to meet the challenges of UHF imaging and the mechanical demands of awake NHP studies.
Elias Djaballah, Éric Giacomini, Paul‐François Gapais, Michel Luong, Alexis Amadon, Qi Zhu   +5 more
wiley   +1 more source

An oversampling-undersampling strategy for large-scale data linkage

Frontiers in Big Data
Effective record linkage in big data, particularly in imbalanced datasets, is a critical yet highly challenging task due to the inherent complexity involved.
Hossein Hassani, Mohammad Reza Entezarian, Sara Zaeimzadeh, Leila Marvian, Nadejda Komendantova   +4 more
doaj   +1 more source

Fast Adaptive Undersampling for Volume Rendering

Journal of WSCG, 2019
Adaptive undersampling is a method for accelerating the rendering process by replacing the calculation of a volume integral with an interpolation procedure for a number of pixels. In this paper, we propose a method for accelerating the volume integral calculation for the rest of the pixels, i.e.
Belyaev, Sergey, Smirnov, Pavel, Smirnova, Natalia, Shubnikov, Vladislav   +3 more
openaire   +2 more sources

Single‐Breathhold 3D MR Elastography in the Liver, With Simultaneous R2* and PDFF Mapping

Magnetic Resonance in Medicine, EarlyView.
Purpose To develop a sequence for the rapid acquisition of MR elastography (MRE) parameters in 3D, with simultaneous measurement of proton‐density fat fraction (PDFF) and R2* for multiparametric assessment of liver disease. Methods The proposed sequence uses an interleaved motion‐encoding scheme to acquire 3D volumes of all motion encodings and wave ...
Donovan P Tripp, Anne‐Sophie van Schelt, Omar Darwish, Karl P Kunze, Shamsa Al Harthy, Nader S Metwalli, Ahmed M Gharib, Claudia Prieto, René M Botnar, Ralph Sinkus, Radhouene Neji   +10 more
wiley   +1 more source