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20182026
most citedSimilarity and Quality Metrics for MR Image-To-Image Translation

66 citations · 122 across the 20 of their papers we have counts for

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eess.IV2026

Revisiting Integration of Image and Metadata for DICOM Series Classification: Cross-Attention and Dictionary Learning

Tuan Truong, Melanie Dohmen, Sara Lorio +1

Automated identification of DICOM image series is essential for large-scale medical image analysis, quality control, protocol harmonization, and reliable downstream processing. How…

eess.IV2024★ 11 cited

Five Pitfalls When Assessing Synthetic Medical Images with Reference Metrics

Melanie Dohmen, Tuan Truong, Ivo M. Baltruschat +1

Reference metrics have been developed to objectively and quantitatively compare two images. Especially for evaluating the quality of reconstructed or compressed images, these metri…

eess.IV2024★ 66 cited

Similarity and Quality Metrics for MR Image-To-Image Translation

Melanie Dohmen, Mark A. Klemens, Ivo M. Baltruschat +2

Image-to-image translation can create large impact in medical imaging, as images can be synthetically transformed to other modalities, sequence types, higher resolutions or lower n…

eess.IV2024

BraSyn 2023 challenge: Missing MRI synthesis and the effect of different learning objectives

Ivo M. Baltruschat, Parvaneh Janbakhshi, Matthias Lenga

This work addresses the Brain Magnetic Resonance Image Synthesis for Tumor Segmentation (BraSyn) challenge, which was hosted as part of the Brain Tumor Segmentation (BraTS) challen…

eess.IV2023

Uncertainty Estimation in Contrast-Enhanced MR Image Translation with Multi-Axis Fusion

Ivo M. Baltruschat, Parvaneh Janbakhshi, Melanie Dohmen +1

In recent years, deep learning has been applied to a wide range of medical imaging and image processing tasks. In this work, we focus on the estimation of epistemic uncertainty for…

eess.IV2023★ 2 cited

fRegGAN with K-space Loss Regularization for Medical Image Translation

Ivo M. Baltruschat, Felix Kreis, Alexander Hoelscher +2

Generative adversarial networks (GANs) have shown remarkable success in generating realistic images and are increasingly used in medical imaging for image-to-image translation task…

eess.IV2020★ 3 cited

Multi-Resolution 3D Convolutional Neural Networks for Automatic Coronary Centerline Extraction in Cardiac CT Angiography Scans

Zohaib Salahuddin, Matthias Lenga, Hannes Nickisch

We propose a deep learning-based automatic coronary artery tree centerline tracker (AuCoTrack) extending the vessel tracker by Wolterink (arXiv:1810.03143). A dual pathway Convolut…