40 citations · 151 across the 14 of their papers we have counts for
15 papers
Low-dimensional embeddings of high-dimensional data
Cyril de Bodt, Alex Diaz-Papkovich, Michael Bleher +18
Large collections of high-dimensional data have become nearly ubiquitous across many academic fields and application domains, ranging from biology to the humanities. Since working…
ManiVault: A Flexible and Extensible Visual Analytics Framework for High-Dimensional Data
Alexander Vieth, Thomas Kroes, Julian Thijssen +7
Exploration and analysis of high-dimensional data are important tasks in many fields that produce large and complex data, like the financial sector, systems biology, or cultural he…
Incorporating Texture Information into Dimensionality Reduction for High-Dimensional Images
Alexander Vieth, Anna Vilanova, Boudewijn Lelieveldt +2
High-dimensional imaging is becoming increasingly relevant in many fields from astronomy and cultural heritage to systems biology. Visual exploration of such high-dimensional data…
Deep Recursive Embedding for High-Dimensional Data
Zixia Zhou, Xinrui Zu, Yuanyuan Wang +2
Embedding high-dimensional data onto a low-dimensional manifold is of both theoretical and practical value. In this paper, we propose to combine deep neural networks (DNN) with mat…
Deep Recursive Embedding for High-Dimensional Data
Zixia Zhou, Yuanyuan Wang, Boudewijn P. F. Lelieveldt +1
t-distributed stochastic neighbor embedding (t-SNE) is a well-established visualization method for complex high-dimensional data. However, the original t-SNE method is nonparametri…
Visual cohort comparison for spatial single-cell omics-data
Antonios Somarakis, Marieke E. Ijsselsteijn, Sietse J. Luk +4
Spatially-resolved omics-data enable researchers to precisely distinguish cell types in tissue and explore their spatial interactions, enabling deep understanding of tissue functio…
An Adaptive Intelligence Algorithm for Undersampled Knee MRI Reconstruction
Nicola Pezzotti, Sahar Yousefi, Mohamed S. Elmahdy +9
Adaptive intelligence aims at empowering machine learning techniques with the additional use of domain knowledge. In this work, we present the application of adaptive intelligence…
Adaptive-CS-Net: FastMRI with Adaptive Intelligence
Nicola Pezzotti, Elwin de Weerdt, Sahar Yousefi +9
Adaptive intelligence aims at empowering machine learning techniques with the extensive use of domain knowledge. In this work, we present the application of adaptive intelligence t…
Hierarchical stochastic neighbor embedding as a tool for visualizing the encoding capability of magnetic resonance fingerprinting dictionaries
Kirsten Koolstra, Peter Börnert, Boudewijn Lelieveldt +2
In Magnetic Resonance Fingerprinting (MRF) the quality of the estimated parameter maps depends on the encoding capability of the variable flip angle train. In this work we show how…
A community-based transcriptomics classification and nomenclature of neocortical cell types
Rafael Yuste, Michael Hawrylycz, Nadia Aalling +68
To understand the function of cortical circuits it is necessary to classify their underlying cellular diversity. Traditional attempts based on comparing anatomical or physiological…
3D Convolutional Neural Networks Image Registration Based on Efficient Supervised Learning from Artificial Deformations
Hessam Sokooti, Bob de Vos, Floris Berendsen +5
We propose a supervised nonrigid image registration method, trained using artificial displacement vector fields (DVF), for which we propose and compare three network architectures.…
Quantitative Error Prediction of Medical Image Registration using Regression Forests
Hessam Sokooti, Gorkem Saygili, Ben Glocker +2
Predicting registration error can be useful for evaluation of registration procedures, which is important for the adoption of registration techniques in the clinic. In addition, qu…
Dynamic vortical flow profile quantitatively characterizes mitral valvular-left ventricular hemodynamic coupling: In vivo analysis by dynamic 3D enstrophy mapping from 4D Flow MRI
Mohammed S. M. Elbaz, Trung Bao Le, Pankaj Garg +6
Vortical blood flow in the human left ventricular (LV) inflow initiates from the mitral valve (MV) and evolves within the LV during diastolic E-filling. Hence, vortical flow links…
GPGPU Linear Complexity t-SNE Optimization
Nicola Pezzotti, Julian Thijssen, Alexander Mordvintsev +5
The t-distributed Stochastic Neighbor Embedding (tSNE) algorithm has become in recent years one of the most used and insightful techniques for the exploratory data analysis of high…
Approximated and User Steerable tSNE for Progressive Visual Analytics
Nicola Pezzotti, Boudewijn P. F. Lelieveldt, Laurens van der Maaten +3
Progressive Visual Analytics aims at improving the interactivity in existing analytics techniques by means of visualization as well as interaction with intermediate results. One ke…