Results 31 to 40 of about 13,919 (263)

An Efficient and Robust Frequency Estimator Dealing With Short-Observation Under-Sampled Waveforms

IEEE Access, 2018
Frequency estimation of a noisy signal in under-sampled conditions is a challenging problem, which has proved to be effectively solved by Chinese remainder theorem (CRT).
Xiangdong Huang, Mengkai Yang, Mingzhuo Liu, Lin Yang   +3 more
doaj   +1 more source

Phase-contrast with interleaved undersampled projections [PDF]

Magnetic Resonance in Medicine, 2000
MR phase-contrast techniques provide velocity-sensitive angiograms and quantitative flow measurements but require long scan times. Recently it has been shown that undersampled projection reconstruction can acquire higher resolution per unit time than Fourier techniques with acceptable artifacts when used in contrast-enhanced MR angiography ...
A V, Barger, D C, Peters, W F, Block, K K, Vigen, F R, Korosec, T M, Grist, C A, Mistretta   +6 more
openaire   +2 more sources

Reliable Parkinson’s Disease Detection by Analyzing Handwritten Drawings: Construction of an Unbiased Cascaded Learning System Based on Feature Selection and Adaptive Boosting Model

IEEE Access, 2019
Parkinson's disease (PD) is the second most common neurodegenerative disease of central nervous system (CNS). Till now, there is no definitive clinical examination that can diagnose a PD patient.
Liaqat Ali, Ce Zhu, Noorbakhsh Amiri Golilarz, Ashir Javeed, Mingyi Zhou, Yipeng Liu   +5 more
doaj   +1 more source

Improving Surgical Site Infection Prediction Using Machine Learning: Addressing Challenges of Highly Imbalanced Data

Diagnostics
Background: Surgical site infections (SSIs) lead to higher hospital readmission rates and healthcare costs, representing a significant global healthcare burden.
Salha Al-Ahmari, Farrukh Nadeem
doaj   +1 more source

Reconstruction of Self-Sparse 2D NMR Spectra from Undersampled Data in the Indirect Dimension

Sensors, 2011
Reducing the acquisition time for two-dimensional nuclear magnetic resonance (2D NMR) spectra is important. One way to achieve this goal is reducing the acquired data.
Zhong Chen, Shuhui Cai, Xue Cao, Di Guo, Xiaobo Qu   +4 more
doaj   +1 more source

Deep Learning Pose Estimation for Phenotyping of Co‐Occurring Hyperkinetic Movement Disorders

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To explore whether routine outpatient video combined with deep learning‐based pose estimation and clinically interpretable kinematic features can support multi‐label phenotyping of co‐occurring hyperkinetic movement disorders (HMDs).
Laura Cif, Diane Demailly, Gabriella A. Horvàth, Juan Dario Ortigoza Escobar, Nathalie Dorison, Mayté Castro Jiménez, Cécile A. Hubsch, Thomas Wirth, Gun‐Marie Hariz, Sophie Huby, Morgan Dornadic, Zohra Souei, Muhammad Mushhood Ur Rehman, Simone Hemm, Mehdi Boulaymen, Eduardo M. Moraud, Jocelyne Bloch, Xavier Vasques   +17 more
wiley   +1 more source

Intelligent Orthopedics: Machine Learning in Diagnosis of Bone Disease, Implants, and Bone Health Monitoring

Advanced Healthcare Materials, EarlyView.
Efficient recovery from traumatic or degenerative diseases is a great challenge, even after all the advancements in bone and cartilage regeneration. Machine learning (ML) algorithms have presented opportunities to enhance these aspects by accurately analyzing imaging data.
Maryam Kamaei, Hesam Mohammadi, Shamim Golafshan, Mojtaba Alehosseini, Mahsa Mohammadzadeh, Atefeh Golshirazi, Nasim Golafshan, Tatiane Eufrásio‐da‐Silva, Alireza Dolatshahi‐Pirouz, Gorka Orive   +9 more
wiley   +1 more source

Orchid Species Classification Using the DenseNet121 Deep Learning Model with a Data Imbalance Handling Approach

Journal of Applied Informatics and Computing
For conservation, commercial cultivation, and scientific research, accurate identification of orchid species often requires specialized expertise.
Fadhilah Aditya Akbar, Christy Atika Sari   +1 more
doaj   +1 more source

Artificial Intelligence‐Assisted Workflow for Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling

Advanced Materials, EarlyView.
AI‐Assisted Workflow for (Scanning) Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling. Abstract (Scanning) transmission electron microscopy ((S)TEM) has significantly advanced materials science but faces challenges in correlating precise atomic structure information with the functional properties of ...
Marc Botifoll, Ivan Pinto‐Huguet, Enzo Rotunno, Thomas Galvani, Catalina Coll, Payam Habibzadeh Kavkani, Maria Chiara Spadaro, Yann‐Michel Niquet, Martin Børstad Eriksen, Sara Martí‐Sánchez, Georgios Katsaros, Giordano Scappucci, Peter Krogstrup, Giovanni Isella, Andreu Cabot, Gonzalo Merino, Pablo Ordejón, Stephan Roche, Vincenzo Grillo, Jordi Arbiol   +19 more
wiley   +1 more source

Neural Fields for Highly Accelerated 2D Cine Phase Contrast MRI

Advanced Science, EarlyView.
ABSTRACT 2D cine phase contrast (CPC) MRI provides quantitative information on blood velocity and flow within the human vasculature. However, data acquisition is time‐consuming, motivating the reconstruction of the velocity field from undersampled measurements to reduce scan times. In this work, neural fields are proposed as a continuous spatiotemporal
Pablo Arratia, Martin J. Graves, Mary McLean, Carolin Pirkl, Carola‐Bibiane Schönlieb, Timo Schirmer, Florian Wiesinger, Matthias J. Ehrhardt   +7 more
wiley   +1 more source