Results 91 to 100 of about 17,625 (278)

Inter‐Shot Motion Correction of Segmented 3D‐GRASE ASL Perfusion Imaging With Self‐Navigation and CAIPI

Magnetic Resonance in Medicine, EarlyView.
ABSTRACT Purpose Segmented 3D Gradient and Spin Echo (GRASE) is commonly used in Arterial Spin Labeling (ASL) perfusion imaging. However, it is vulnerable to inter‐shot motion, leading to subtraction errors that cannot be corrected. We developed a retrospective self‐navigated inter‐shot motion correction method for segmented 3D‐GRASE ASL imaging with ...
Minhao Hu, Frederik J. Lange, Peter Jezzard, Joseph G. Woods, Mark Chiew, Thomas W. Okell   +5 more
wiley   +1 more source

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

Applying undersampling to the nuclear magnetic resonance signal [PDF]

, 1996
Proceedings of: 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Amsterdam, 31 Oct. - 03 Nov. 1996.This paper presents the use of undersampling in an NMR prototype equipment.
Pozo, Francisco del, Pérez, Pablo, Vaquero, Juan José, Rivera, Manuel, Santos, Andrés, Vaquero López, Juan José   +5 more
core   +1 more source

Collaborative Reconstruction of PROPELLER‐EPI Data Using POCSMUSE (CORPUSE) for High‐Fidelity Diffusion MRI

Magnetic Resonance in Medicine, EarlyView.
ABSTRACT Purpose To develop a reconstruction framework for DW‐PROPELLER‐EPI that improves image quality and SNR efficiency under per‐blade acceleration while minimizing EPI‐related artifacts, enabling high‐resolution diffusion‐tensor imaging (DTI) with fewer blades.
Hailin Xiong, Liyuan Liang, Shihui Chen, Yi Li, Chenglang Yuan, Tianbaige Liu, Xiaorui Xu, Hing‐Chiu Chang   +7 more
wiley   +1 more source

Analysis of Nonidealities in Undersampling SAR ADCs

, 2018
With the foreseeable adaptation of 5 G networks and its increasing use, blockers are becoming more common on their frequency bands. This gives rise to the need of wideband blocker-detection circuits for frequencies up to 6 GHz. The use of under- sampling
Mattersdorfer, Clemens
core  

BART Streams: Real‐Time Reconstruction Using a Modular Framework for Pipeline Processing

Magnetic Resonance in Medicine, EarlyView.
ABSTRACT Purpose To create modular solutions for interactive real‐time MRI using reconstruction algorithms implemented in BART. Methods A new protocol for streaming of multidimensional arrays is presented and integrated into BART. The new functionality is demonstrated using examples for cardiac interactive real‐time MRI based on radial FLASH, where ...
Philip Schaten, Moritz Blumenthal, Bernhard Rapp, Christina Unterberg‐Buchwald, Martin Uecker   +4 more
wiley   +1 more source

Undersampling GA-SVM for network intrusion detection

, 2017
Network intrusion detection is one of the hottest issues in the world. An increasing number of researchers and engineers deal with this problem by using machine learning methods.
He, Zhenyu
core  

Undersampling to accelerate time-resolved MRI velocity measurement of carotid blood flow [PDF]

, 2009
Time-resolved velocity information of carotid blood flow can be used to estimate haemodynamic conditions associated with carotid artery disease leading to stroke.
Tao, Yuehui
core   +1 more source

Methods for Uncertainty Quantification in Dictionary Matching to Advance Reliability of Quantitative MRI

Magnetic Resonance in Medicine, EarlyView.
ABSTRACT Aims Purpose: Dictionary matching is a standard tool in quantitative MRI (qMRI), but typically lacks uncertainty quantification (UQ). This is critical when advanced reconstructions (e.g., compressed sensing, deep learning) introduce complex‐valued, spatially varying, and temporally correlated noise that violates standard assumptions of ...
Brian Toner, Ute Goerke, Eze Ahanonu, Kevin Johnson, Vibhas Deshpande, Holden H. Wu, Maria I. Altbach, Ali Bilgin   +7 more
wiley   +1 more source

A combined imbalanced classification approach based on D-S Evidence Theory and its application in network traffic recognition

Dianxin kexue
The imbalanced classification problem is one of the common challenges in machine learning and widely exists in practical applications such as network traffic recognition.
HE Hongshun, HU Guoliang, ZHANG Zhipeng, CHAI Xingang, GAO Jing   +4 more
doaj   +2 more sources