Deep Recursive Embedding for High-Dimensional Data

1 code implementation • 31 Oct 2021 • Zixia Zhou, Xinrui Zu, Yuanyuan Wang, Boudewijn P. F. Lelieveldt, Qian Tao

Embedding high-dimensional data onto a low-dimensional manifold is of both theoretical and practical value.

Vocal Bursts Intensity Prediction

Deep Recursive Embedding for High-Dimensional Data

no code implementations • 12 Apr 2021 • Zixia Zhou, Yuanyuan Wang, Boudewijn P. F. Lelieveldt, Qian Tao

t-distributed stochastic neighbor embedding (t-SNE) is a well-established visualization method for complex high-dimensional data.

Vocal Bursts Intensity Prediction

An Adaptive Intelligence Algorithm for Undersampled Knee MRI Reconstruction

no code implementations • 15 Apr 2020 • Nicola Pezzotti, Sahar Yousefi, Mohamed S. Elmahdy, Jeroen van Gemert, Christophe Schülke, Mariya Doneva, Tim Nielsen, Sergey Kastryulin, Boudewijn P. F. Lelieveldt, Matthias J. P. van Osch, Elwin de Weerdt, Marius Staring

In this work, we present the application of adaptive intelligence to accelerate MR acquisition.

MRI Reconstruction

Linking convolutional neural networks with graph convolutional networks: application in pulmonary artery-vein separation

1 code implementation • Preprint 2019 • Zhiwei Zhai, Marius Staring, Xuhui Zhou, Qiuxia Xie, Xiaojuan Xiao, M. Els Bakker, Lucia J. Kroft, Boudewijn P. F. Lelieveldt, Gudula J.A.M. Boon, Frederikus A. Klok, Berend C. Stoel

In conclusion, the proposed CNN-GCN method combines local image information with graph connectivity information, improving pulmonary A/V separation over a baseline CNN method, approaching the performance of human observers.

3D Medical Imaging Segmentation Pulmonary Artery–Vein Classification

3D Convolutional Neural Networks Image Registration Based on Efficient Supervised Learning from Artificial Deformations

1 code implementation • 27 Aug 2019 • Hessam Sokooti, Bob de Vos, Floris Berendsen, Mohsen Ghafoorian, Sahar Yousefi, Boudewijn P. F. Lelieveldt, Ivana Isgum, Marius Staring

We propose a supervised nonrigid image registration method, trained using artificial displacement vector fields (DVF), for which we propose and compare three network architectures.

Image Registration

Quantitative Error Prediction of Medical Image Registration using Regression Forests

1 code implementation • 18 May 2019 • Hessam Sokooti, Gorkem Saygili, Ben Glocker, Boudewijn P. F. Lelieveldt, Marius Staring

This paper proposes a new automatic method to predict the registration error in a quantitative manner, and is applied to chest CT scans.

Image Registration Medical Image Registration +1

GPGPU Linear Complexity t-SNE Optimization

1 code implementation • 28 May 2018 • Nicola Pezzotti, Julian Thijssen, Alexander Mordvintsev, Thomas Hollt, Baldur van Lew, Boudewijn P. F. Lelieveldt, Elmar Eisemann, Anna Vilanova

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-dimensional data.

Approximated and User Steerable tSNE for Progressive Visual Analytics

no code implementations • 5 Dec 2015 • Nicola Pezzotti, Boudewijn P. F. Lelieveldt, Laurens van der Maaten, Thomas Höllt, Elmar Eisemann, Anna Vilanova

Progressive Visual Analytics aims at improving the interactivity in existing analytics techniques by means of visualization as well as interaction with intermediate results.

Dimensionality Reduction