38 citations · 55 across the 3 of their papers we have counts for
9 papers
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.…