Results 31 to 40 of about 17,625 (278)

Mitigating undersampling errors in MR fingerprinting by sequence optimization

, 2022
Purpose: To develop a method for MR Fingerprinting (MRF) sequence optimization that takes both the applied undersampling pattern and a realistic reference map into account.
Koolstra, Kirsten (author), Heesterbeek, D.G.J., Osch, M.J.P. van, van Osch, Matthias J.P., Martijn A. Nagtegaal, David G.J. Heesterbeek, Gijzen, M.B. van, van Gijzen, M.B. (author), Heesterbeek, David G.J., Vos, F.M. (author), Koolstra, K., Vos, F.M., Nagtegaal, M.A., Heesterbeek, David G.J. (author), Matthias J.P. van Osch, van Osch, Matthias J.P. (author), Nagtegaal, M.A. (author), Koolstra, Kirsten, Martin B. van Gijzen, Franciscus M. Vos, van Gijzen, M.B., Kirsten Koolstra   +21 more
core   +1 more source

Evaluating Landslide Susceptibility Using Sampling Methodology and Multiple Machine Learning Models

ISPRS International Journal of Geo-Information, 2023
Landslide susceptibility assessment (LSA) based on machine learning methods has been widely used in landslide geological hazard management and research.
Yingze Song, Degang Yang, Weicheng Wu, Xin Zhang, Jie Zhou, Zhaoxu Tian, Chencan Wang, Yingxu Song   +7 more
doaj   +1 more source

Selecting the Suitable Resampling Strategy for Imbalanced Data Classification Regarding Dataset Properties. An Approach Based on Association Models

Applied Sciences, 2021
In many application domains such as medicine, information retrieval, cybersecurity, social media, etc., datasets used for inducing classification models often have an unequal distribution of the instances of each class.
Mohamed S. Kraiem, Fernando Sánchez-Hernández, María N. Moreno-García   +2 more
doaj   +1 more source

MRF undersampling optimization: Software and code for the publication: Mitigating undersampling errors in Magnetic Resonance Fingerprinting by sequence optimization

, 2022
Repository to perform sequence optimization as proposed in the following paper: Mitigating undersampling errors in Magnetic Resonance Fingerprinting by sequence optimization D.G.J. Heesterbeek, K. Koolstra, M.J.P. van Osch, M.B. van Gijzen, F.M.
Martijn Nagtegaal (12278942), David Heesterbeek (12895770)   +1 more
core   +1 more source

Learning from Imbalanced Data Using an Evidential Undersampling-Based Ensemble

, 2022
International audienceIn many real-world binary classification problems, one class tends to be heavily underrepresented when it consists of far fewer observations than the other class. This results in creating a biased model with undesirable performance.
Lefevre, Eric, Grina, Fares, Elouedi, Zied   +2 more
core   +1 more source

Utilizing logistic regression to compare risk factors in disease modeling with imbalanced data: a case study in vitamin D and cancer incidence

Frontiers in Oncology, 2023
Imbalanced data, a common challenge encountered in statistical analyses of clinical trial datasets and disease modeling, refers to the scenario where one class significantly outnumbers the other in a binary classification problem. This imbalance can lead
Mohammad Meysami, Vijay Kumar, McKayah Pugh, Samuel Thomas Lowery, Shantanu Sur, Sumona Mondal, James M. Greene   +6 more
doaj   +1 more source

Undersampling masks.

, 2019
An example of representative undersampling masks for different undersampling factors, together with the magnitude data from the CS reconstructions.
Jan Magnus Aronsen (347485), Lili Zhang (120447), Ivar Sjaastad (162165), Gary McGinley (6919646), Bård A. Bendiksen (6919649), Einar Sjaastad Nordén (6919652), Emil K. S. Espe (6919655)   +6 more
core   +1 more source

Pengembangan Prediksi Kerusakan Perangkat Lunak Menggunakan Kombinasi Oversampling dan Undersampling [PDF]

, 2022
Kualitas perangkat lunak dapat ditingkatkan dengan melakukan pengujian perangkat lunak, akan tetapi semakin banyak fitur yang dikembangkan semakin banyak juga sumber daya yang dibutuhkan. Karena itu prediksi kecacatan perangkat lunak (SDP) diperkenalkan.
Iswafaza, Aizul Faiz
core  

Beyond Nyquist: A Comparative Analysis of 3D Deep Learning Models Enhancing MRI Resolution

Journal of Imaging
High-spatial resolution MRI produces abundant structural information, enabling highly accurate clinical diagnosis and image-guided therapeutics. However, the acquisition of high-spatial resolution MRI data typically can come at the expense of less ...
Soumick Chatterjee, Alessandro Sciarra, Max Dünnwald, Anitha Bhat Talagini Ashoka, Mayura Gurjar Cheepinahalli Vasudeva, Shudarsan Saravanan, Venkatesh Thirugnana Sambandham, Pavan Tummala, Steffen Oeltze-Jafra, Oliver Speck, Andreas Nürnberger   +10 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