Explanipedia

Efficient Maximum Euclidean Distance Transform Computation in Component Trees Using the Differential Image Foresting Transform Open

Dennis J. Silva, Paulo A. V. Miranda, Wonder Alexandre Luz Alves, Ronaldo F. Hashimoto, Jiří Kosinka , et al. · 2025

HyperFLINT: Hypernetwork‐based Flow Estimation and Temporal Interpolation for Scientific Ensemble Visualization Open

Hamid Gadirov, Qi Wu, David R. Bauer, Kwan‐Liu Ma, Jos B. T. M. Roerdink , et al. · 2025

We present HyperFLINT (Hypernetwork‐based FLow estimation and temporal INTerpolation), a novel deep learning‐based approach for estimating flow fields, temporally interpolating scalar fields, and facilitating parameter space exploration in…

BoneStory: Visual Storytelling in 3D Virtual Surgical Planning for Bone Fracture Reduction Open

H. Lee, Peter A. J. Pijpker, Joep Kraeima, Lorenzo Amabili, Fokie Cnossen , et al. · 2025

HyperFLINT: Hypernetwork-based Flow Estimation and Temporal Interpolation for Scientific Ensemble Visualization Open

Hamid Gadirov, Qi Wu, David R. Bauer, Kwan‐Liu Ma, Jos B. T. M. Roerdink , et al. · 2024

We present HyperFLINT (Hypernetwork-based FLow estimation and temporal INTerpolation), a novel deep learning-based approach for estimating flow fields, temporally interpolating scalar fields, and facilitating parameter space exploration in…

Incremental component tree contour computation Open

Dennis J. Silva, Jiří Kosinka, Ronaldo F. Hashimoto, Jos B. T. M. Roerdink, Alexandre Morimitsu , et al. · 2024

A component tree is a graph representation that encodes the connected components of the upper or lower level sets of a grayscale image. Consequently, the nodes of a component tree represent binary images of the encoded connected components…

FLINT: Learning-based Flow Estimation and Temporal Interpolation for Scientific Ensemble Visualization Open

Hamid Gadirov, Jos B. T. M. Roerdink, Steffen Frey · 2024

We present FLINT (learning-based FLow estimation and temporal INTerpolation), a novel deep learning-based approach to estimate flow fields for 2D+time and 3D+time scientific ensemble data. FLINT can flexibly handle different types of scena…

Supervised star, galaxy, and QSO classification with sharpened dimensionality reduction Open

Marten Lourens, S. C. Trager, Y. Kim, Alexandru Telea, Jos B. T. M. Roerdink · 2024

Aims. We explored the use of broadband colors to classify stars, galaxies, and quasi-stellar objects (QSOs). Specifically, we applied sharpened dimensionality reduction (SDR)-aided classification to this problem, with the aim of enhancing …

Image vectorization using a sparse patch layout Open

Kefeng He, Jos B. T. M. Roerdink, Jiří Kosinka · 2024

Stripe noise removal in conductive atomic force microscopy Open

Mian Li, Jan Rieck, Beatriz Noheda, Jos B. T. M. Roerdink, Michael H. F. Wilkinson · 2024

Differential Maximum Euclidean Distance Transform Computation in Component Trees Open

Dennis J. Silva, Paulo A. V. Miranda, Wonder Alexandre Luz Alves, Ronaldo F. Hashimoto, Jiří Kosinka , et al. · 2024

Stripe Noise Removal in Scanning Probe Microscopy Open

Mian Li, Jan Rieck, Beatriz Noheda, Jos B. T. M. Roerdink, Michael H. F. Wilkinson · 2023

Conductive atomic force microscopy (c-AFM) can provide simultaneous maps of the topography and electrical current flow through materials with high spacial resolution and it is playing an increasingly important role in the characterization …

Stabilizing and Simplifying Sharpened Dimensionality Reduction Using Deep Learning Open

Mateus Espadoto, Youngjoo Kim, S. C. Trager, Jos B. T. M. Roerdink, Alexandru Telea · 2023

Interactive image manipulation using morphological trees and spline-based skeletons Open

Jieying Wang, Dennis J. Silva, Jiří Kosinka, Alexandru Telea, Ronaldo F. Hashimoto , et al. · 2022

The ability to edit an image using intuitive commands and primitives is a desired feature for any image editing software. In this paper, we combine recent results in medial axes with the well-established morphological tree representations …

Visual cluster separation using high-dimensional sharpened dimensionality reduction Open

Youngjoo Kim, Alexandru Telea, S. C. Trager, Jos B. T. M. Roerdink · 2022

Applying dimensionality reduction (DR) to large, high-dimensional data sets can be challenging when distinguishing the underlying high-dimensional data clusters in a 2D projection for exploratory analysis. We address this problem by first …

Human Motion Detection Using Sharpened Dimensionality Reduction and Clustering Open

Jeewon Heo, Youngjoo Kim, Jos B. T. M. Roerdink · 2022

Sharpened dimensionality reduction (SDR), which belongs to the class of multidimensional projection techniques, has recently been introduced to tackle the challenges in the exploratory and visual analysis of high-dimensional data. SDR has …

SDR-NNP: Sharpened Dimensionality Reduction with Neural Networks Open

Youngjoo Kim, Mateus Espadoto, S. C. Trager, Jos B. T. M. Roerdink, Alexandru Telea · 2022

Dimensionality reduction (DR) methods aim to map high-dimensional datasets to 2D scatterplots for visual exploration. Such scatterplots are used to reason about the cluster structure of the data, so creating well-separated visual clusters …

Michel Westenberg (1973–2021) Open

Jos B. T. M. Roerdink, Jarke J. van Wijk · 2021

Recounts the career and contributions of Michel Westenberg.

Visual Cluster Separation Using High-Dimensional Sharpened Dimensionality Reduction Open

Youngjoo Kim, Alexandru Telea, S. C. Trager, Jos B. T. M. Roerdink · 2021

Applying dimensionality reduction (DR) to large, high-dimensional data sets can be challenging when distinguishing the underlying high-dimensional data clusters in a 2D projection for exploratory analysis. We address this problem by first …

Scientific Visualisation of Extremely Large Distributed Astronomical Surveys Open

S. Singh, E. A. Valentijn, A. N. Belikov, Hugo Buddelmeijer, Jos B. T. M. Roerdink · 2020

Visualizing High-Dimensional Chemical Abundance Space in GALAH DR2 Open

Youngjoo Kim, S. C. Trager, Alexandru Telea, Jos B. T. M. Roerdink · 2019

Corrigendum to “Group morphology” [Pattern Recognition 33(6) (2000) 877–895] Open

Jos B. T. M. Roerdink · 2019

Comparison of Brain Connectivity Networks Using Local Structure Analysis Open

Chengtao Ji, Natasha M. Maurits, Jos B. T. M. Roerdink · 2018

Visual Exploration of Dynamic Multichannel EEG Coherence Networks Open

Chengtao Ji, Jasper J. van de Gronde, Natasha M. Maurits, Jos B. T. M. Roerdink · 2018

Electroencephalography (EEG) coherence networks represent functional brain connectivity, and are constructed by calculating the coherence between pairs of electrode signals as a function of frequency. Visualization of such networks can pro…

Distinguishing Patients With a Coordination Disorder From Healthy Controls Using Local Features of Movement Trajectories During the Finger-to-Nose Test Open

Venustiano Soancatl Aguilar, Octavio Martinez Manzanera, Deborah A. Sival, Natasha M. Maurits, Jos B. T. M. Roerdink · 2018

Assessment of coordination disorders is valuable for monitoring progression of patients, distinguishing healthy and pathological conditions, and ultimately aiding in clinical decision making, thereby offering the possibility to improve med…

Mathematical Morphology with Noncommutative Symmetry Groups Open

Jos B. T. M. Roerdink · 2018

This chapter reviews Euclidean morphology together with some lattice-theoretical concepts. It introduces the concept of homogeneous spaces, and explores Euclidean morphology to the Boolean lattice of all subsets of an arbitrary group, orde…

Data-driven visualization of multichannel EEG coherence networks based on community structure analysis Open

Chengtao Ji, Natasha M. Maurits, Jos B. T. M. Roerdink · 2018

Visual Analysis of Evolution of EEG Coherence Networks employing Temporal Multidimensional Scaling Open

Chengtao Ji, Natasha M. Maurits, Jos B. T. M. Roerdink · 2018

The community structure of networks plays an important role in their analysis. It represents a high-level organization of objects within a network. However, in many application domains, the relationship between objects in a network changes…

Improving Provenance Data Interaction for Visual Storytelling in Medical Imaging Data Exploration Open

Lorenzo Amabili, Jiří Kosinka, Maarten A.J. van Meersbergen, Peter M. A. van Ooijen, Jos B. T. M. Roerdink , et al. · 2018

Effective collaborative work in diagnostic medical imaging is not trivial due to the large amounts of complex data involved, a (non-linear) workflow involving experts in different domains, and a lack of versatility in the current tools emp…

Machine Learning Based Analysis of FDG-PET Image Data for the Diagnosis of Neurodegenerative Diseases Open

Rick van Veen, Lidia Talavera-Martínez, Rosalie V. Kogan, Sanne K. Meles, Deborah Mudali , et al. · 2018

Alzheimer's disease (AD) and Parkinson's disease (PD) are two common, progressive neurodegenerative brain disorders. Their diagnosis is very challenging at an early disease stage, if based on clinical symptoms only. Brain imaging technique…

Assessing dynamic postural control during exergaming in older adults: A probabilistic approach Open

Venustiano Soancatl Aguilar, Claudine J. C. Lamoth, Natasha M. Maurits, Jos B. T. M. Roerdink · 2017

Jos B. T. M. Roerdink YOU? Author Swipe