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20202026
most citedMulti-Center Fetal Brain Tissue Annotation (FeTA) Challenge 2022 Results

23 citations · 26 across the 13 of their papers we have counts for

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eess.IV2026

Implicit representations are dead. Long live explicit primitives!

Nil Stolt-Ansó, Maik Dannecker, Wenqi Huang +2

Continuous parameterization of medical data has emerged as a powerful paradigm for resolution-independent image representation. While Implicit Neural Representations offer high fid…

eess.IV2026

Gabor Primitives for Accelerated Cardiac Cine MRI Reconstruction

Wenqi Huang, Veronika Spieker, Nil Stolt-Ansó +6

Accelerated cardiac cine MRI requires reconstructing spatiotemporal images from highly undersampled k-space data. Implicit neural representations (INRs) enable scan-specific recons…

eess.IV2025

Meta-learning Slice-to-Volume Reconstruction in Fetal Brain MRI using Implicit Neural Representations

Maik Dannecker, Thomas Sanchez, Meritxell Bach Cuadra +6

High-resolution slice-to-volume reconstruction (SVR) from multiple motion-corrupted low-resolution 2D slices constitutes a critical step in image-based diagnostics of moving subjec…

eess.IV2024

Intensity-based 3D motion correction for cardiac MR images

Nil Stolt-Ansó, Vasiliki Sideri-Lampretsa, Maik Dannecker +1

Cardiac magnetic resonance (CMR) image acquisition requires subjects to hold their breath while 2D cine images are acquired. This process assumes that the heart remains in the same…

eess.IV2024★ 23 cited

Multi-Center Fetal Brain Tissue Annotation (FeTA) Challenge 2022 Results

Kelly Payette, Céline Steger, Roxane Licandro +64

Segmentation is a critical step in analyzing the developing human fetal brain. There have been vast improvements in automatic segmentation methods in the past several years, and th…

eess.IV2023★ 1 cited

Single-subject Multi-contrast MRI Super-resolution via Implicit Neural Representations

Julian McGinnis, Suprosanna Shit, Hongwei Bran Li +9

Clinical routine and retrospective cohorts commonly include multi-parametric Magnetic Resonance Imaging; however, they are mostly acquired in different anisotropic 2D views due to…

eess.IV2020★ 2 cited

Multi-Coil MRI Reconstruction Challenge -- Assessing Brain MRI Reconstruction Models and their Generalizability to Varying Coil Configurations

Youssef Beauferris, Jonas Teuwen, Dimitrios Karkalousos +20

Deep-learning-based brain magnetic resonance imaging (MRI) reconstruction methods have the potential to accelerate the MRI acquisition process. Nevertheless, the scientific communi…