9 citations · 13 across the 13 of their papers we have counts for
16 papers
AxonSynth: Domain-Randomized Synthetic Data for Zero-Shot 3D Axon Segmentation in Light-Sheet Microscopy
Edward Gaibor, Kyriaki-Margarita Bintsi, Carmen Luz Leiva Ureta +9
Accurate segmentation of axons in 3D microscopy data is important for analyzing white-matter organization, but dense ground truth labels are expensive to obtain. Existing supervise…
Topology-Aware Training and Spatial Diagnostics for Fiber Bundle Segmentation in Tracer Histology
Joselyn Romero Avila, Kyriaki-Margarita Bintsi, Ermias Habte +3
Anatomic tracer studies reveal how axon bundles project from an injection site, branch into smaller groups of axons, and course through the brain to reach their destinations. Histo…
Tractography-Driven Synthetic Data Generation for Fiber Bundle Segmentation in Tracer Histology
Kyriaki-Margarita Bintsi, Sparsh Makharia, Yaël Balbastre +4
Diffusion MRI (dMRI) tractography enables non-invasive reconstruction of white-matter pathways, but its accuracy is fundamentally limited by indirect, low-resolution measurements o…
Global 3D Reconstruction of Clouds & Tropical Cyclones
Shirin Ermis, Cesar Aybar, Lilli Freischem +7
Accurate forecasting of tropical cyclones (TCs) remains challenging due to limited satellite observations probing TC structure and difficulties in resolving cloud properties involv…
Fully Automated Segmentation of Fiber Bundles in Anatomic Tracing Data
Kyriaki-Margarita Bintsi, Yaël Balbastre, Jingjing Wu +3
Anatomic tracer studies are critical for validating and improving diffusion MRI (dMRI) tractography. However, large-scale analysis of data from such studies is hampered by the labo…
3D Cloud reconstruction through geospatially-aware Masked Autoencoders
Stella Girtsou, Emiliano Diaz Salas-Porras, Lilli Freischem +7
Clouds play a key role in Earth's radiation balance with complex effects that introduce large uncertainties into climate models. Real-time 3D cloud data is essential for improving…
SuNeRF: 3D reconstruction of the solar EUV corona using Neural Radiance Fields
Robert Jarolim, Benoit Tremblay, Andrés Muñoz-Jaramillo +8
To understand its evolution and the effects of its eruptive events, the Sun is permanently monitored by multiple satellite missions. The optically-thin emission of the solar plasma…
A Comparative Study of Population-Graph Construction Methods and Graph Neural Networks for Brain Age Regression
Kyriaki-Margarita Bintsi, Tamara T. Mueller, Sophie Starck +3
The difference between the chronological and biological brain age of a subject can be an important biomarker for neurodegenerative diseases, thus brain age estimation can be crucia…
Multimodal brain age estimation using interpretable adaptive population-graph learning
Kyriaki-Margarita Bintsi, Vasileios Baltatzis, Rolandos Alexandros Potamias +2
Brain age estimation is clinically important as it can provide valuable information in the context of neurodegenerative diseases such as Alzheimer's. Population graphs, which inclu…
Extended Graph Assessment Metrics for Graph Neural Networks
Tamara T. Mueller, Sophie Starck, Leonhard F. Feiner +3
When re-structuring patient cohorts into so-called population graphs, initially independent data points can be incorporated into one interconnected graph structure. This population…
SuNeRF: Validation of a 3D Global Reconstruction of the Solar Corona Using Simulated EUV Images
Kyriaki-Margarita Bintsi, Robert Jarolim, Benoit Tremblay +8
Extreme Ultraviolet (EUV) light emitted by the Sun impacts satellite operations and communications and affects the habitability of planets. Currently, EUV-observing instruments are…
GraphWalks: Efficient Shape Agnostic Geodesic Shortest Path Estimation
Rolandos Alexandros Potamias, Alexandros Neofytou, Kyriaki-Margarita Bintsi +1
Geodesic paths and distances are among the most popular intrinsic properties of 3D surfaces. Traditionally, geodesic paths on discrete polygon surfaces were computed using shortest…
Voxel-level Importance Maps for Interpretable Brain Age Estimation
Kyriaki-Margarita Bintsi, Vasileios Baltatzis, Alexander Hammers +1
Brain aging, and more specifically the difference between the chronological and the biological age of a person, may be a promising biomarker for identifying neurodegenerative disea…
The Pitfalls of Sample Selection: A Case Study on Lung Nodule Classification
Vasileios Baltatzis, Kyriaki-Margarita Bintsi, Loic Le Folgoc +6
Using publicly available data to determine the performance of methodological contributions is important as it facilitates reproducibility and allows scrutiny of the published resul…
The Effect of the Loss on Generalization: Empirical Study on Synthetic Lung Nodule Data
Vasileios Baltatzis, Loic Le Folgoc, Sam Ellis +6
Convolutional Neural Networks (CNNs) are widely used for image classification in a variety of fields, including medical imaging. While most studies deploy cross-entropy as the loss…
Patch-based Brain Age Estimation from MR Images
Kyriaki-Margarita Bintsi, Vasileios Baltatzis, Arinbjörn Kolbeinsson +2
Brain age estimation from Magnetic Resonance Images (MRI) derives the difference between a subject's biological brain age and their chronological age. This is a potential biomarker…