313 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Friedrich-Alexander-Universität Erlangen-NürnbergDE41 papers
- Siemens Healthcare (United States)US17 papers
- Siemens (United States)US11 papers
- Technical University of MunichDE4 papers
- Heidelberg UniversityDE3 papers
- King's College LondonGB3 papers
- Siemens (Germany)DE3 papers
- Stanford UniversityUS3 papers
- Advanced Optical Technologies (United States)US2 papers
- Blekinge Institute of TechnologySE2 papers
- Centre d'Imagerie BioMedicaleCH2 papers
- Columbia UniversityUS2 papers
76 papers
Cut to the Mix: Simple Data Augmentation Outperforms Elaborate Ones in Limited Organ Segmentation Datasets
Chang Liu, Fuxin Fan, Annette Schwarz +1
Multi-organ segmentation is a widely applied clinical routine and automated organ segmentation tools dramatically improve the pipeline of the radiologists. Recently, deep learning…
Exemplar Med-DETR: Toward Generalized and Robust Lesion Detection in Mammogram Images and beyond
Sheethal Bhat, Bogdan Georgescu, Adarsh Bhandary Panambur +8
Detecting abnormalities in medical images poses unique challenges due to differences in feature representations and the intricate relationship between anatomical structures and abn…
Multi-Plane Vision Transformer for Hemorrhage Classification Using Axial and Sagittal MRI Data
Badhan Kumar Das, Gengyan Zhao, Boris Mailhe +4
Identifying brain hemorrhages from magnetic resonance imaging (MRI) is a critical task for healthcare professionals. The diverse nature of MRI acquisitions with varying contrasts a…
Evaluation of a Novel Quantitative Multiparametric MR Sequence for Radiation Therapy Treatment Response Assessment
Yuhao Yan, R. Adam Bayliss, Adam R. Burr +5
Purpose: To evaluate a Deep-Learning-enhanced MUlti-PArametric MR sequence (DL-MUPA) for treatment response assessment for brain metastases patients undergoing stereotactic radiosu…
SAMRI-2: A Memory-based Model for Cartilage and Meniscus Segmentation in 3D MRIs of the Knee Joint
Danielle L. Ferreira, Bruno A. A. Nunes, Xuzhe Zhang +3
Accurate morphometric assessment of cartilage-such as thickness/volume-via MRI is essential for monitoring knee osteoarthritis. Segmenting cartilage remains challenging and depende…
A Novel Tracking Framework for Devices in X-ray Leveraging Supplementary Cue-Driven Self-Supervised Features
Saahil Islam, Venkatesh N. Murthy, Dominik Neumann +5
To restore proper blood flow in blocked coronary arteries via angioplasty procedure, accurate placement of devices such as catheters, balloons, and stents under live fluoroscopy or…
A Realistic Collimated X-Ray Image Simulation Pipeline
Benjamin El-Zein, Dominik Eckert, Thomas Weber +4
Collimator detection remains a challenging task in X-ray systems with unreliable or non-available information about the detectors position relative to the source. This paper presen…
Model-Based Perfusion Reconstruction with Time Separation Technique in Cone-Beam CT Dynamic Liver Perfusion Imaging
Hana Haseljić, Robert Frysch, Vojtěch Kulvait +6
The success of embolisation, a minimally invasive treatment of liver cancer, could be evaluated in the operational room with cone-beam CT by acquiring a dynamic perfusion scan. The…
Multi-Layer Gaussian Splatting for Immersive Anatomy Visualization
Constantin Kleinbeck, Hannah Schieber, Klaus Engel +2
In medical image visualization, path tracing of volumetric medical data like CT scans produces lifelike three-dimensional visualizations. Immersive VR displays can further enhance…
Towards a vision foundation model for comprehensive assessment of Cardiac MRI
Athira J Jacob, Indraneel Borgohain, Teodora Chitiboi +3
Cardiac magnetic resonance imaging (CMR), considered the gold standard for noninvasive cardiac assessment, is a diverse and complex modality requiring a wide variety of image proce…
StoDIP: Efficient 3D MRF image reconstruction with deep image priors and stochastic iterations
Perla Mayo, Matteo Cencini, Carolin M. Pirkl +4
Magnetic Resonance Fingerprinting (MRF) is a time-efficient approach to quantitative MRI for multiparametric tissue mapping. The reconstruction of quantitative maps requires tailor…
High-Dimensional Confidence Regions in Sparse MRI
Frederik Hoppe, Felix Krahmer, Claudio Mayrink Verdun +2
One of the most promising solutions for uncertainty quantification in high-dimensional statistics is the debiased LASSO that relies on unconstrained -minimization. The init…
Physics-Informed Learning for Time-Resolved Angiographic Contrast Agent Concentration Reconstruction
Noah Maul, Annette Birkhold, Fabian Wagner +5
Three-dimensional Digital Subtraction Angiography (3D-DSA) is a well-established X-ray-based technique for visualizing vascular anatomy. Recently, four-dimensional DSA (4D-DSA) rec…
A gradient-based approach to fast and accurate head motion compensation in cone-beam CT
Mareike Thies, Fabian Wagner, Noah Maul +9
Cone-beam computed tomography (CBCT) systems, with their flexibility, present a promising avenue for direct point-of-care medical imaging, particularly in critical scenarios such a…
AI-based, automated chamber volumetry from gated, non-contrast CT
Athira J Jacob, Ola Abdelkarim, Salma Zook +11
Background: Accurate chamber volumetry from gated, non-contrast cardiac CT (NCCT) scans can be useful for potential screening of heart failure. Objectives: To validate a new, fully…
Validation of apparent intra-and extra-myocellular lipid content indicator using spiral spectroscopic imaging at 3T
Antoine Naëgel, Magalie Viallon, Jabrane Karkouri +3
This work presents a fast and simple method based on spiral MRSI for mapping the IMCL and EMCL apparent content, which is a challenging task and it compares this indicator to class…
Evaluation and Measurement of Software Process Improvement -- A Systematic Literature Review
Michael Unterkalmsteiner, Tony Gorschek, A. K. M. Moinul Islam +3
BACKGROUND: Software Process Improvement (SPI) is a systematic approach to increase the efficiency and effectiveness of a software development organization and to enhance software…
A conceptual framework for SPI evaluation
Michael Unterkalmsteiner, Tony Gorschek, A. K. M. Moinul Islam +3
Software Process Improvement (SPI) encompasses the analysis and modification of the processes within software development, aimed at improving key areas that contribute to the organ…
Anatomically aware dual-hop learning for pulmonary embolism detection in CT pulmonary angiograms
Florin Condrea, Saikiran Rapaka, Lucian Itu +4
Pulmonary Embolisms (PE) represent a leading cause of cardiovascular death. While medical imaging, through computed tomographic pulmonary angiography (CTPA), represents the gold st…
Transient Hemodynamics Prediction Using an Efficient Octree-Based Deep Learning Model
Noah Maul, Katharina Zinn, Fabian Wagner +6
Patient-specific hemodynamics assessment could support diagnosis and treatment of neurovascular diseases. Currently, conventional medical imaging modalities are not able to accurat…
Gradient-Based Geometry Learning for Fan-Beam CT Reconstruction
Mareike Thies, Fabian Wagner, Noah Maul +10
Incorporating computed tomography (CT) reconstruction operators into differentiable pipelines has proven beneficial in many applications. Such approaches usually focus on the proje…
Hybrid adiabatic quantum computing for tomographic image reconstruction -- opportunities and limitations
Merlin A. Nau, A. Hans Vija, Wesley Gohn +2
Our goal is to reconstruct tomographic images with few measurements and a low signal-to-noise ratio. In clinical imaging, this helps to improve patient comfort and reduce radiation…
Biomedical image analysis competitions: The state of current participation practice
Matthias Eisenmann, Annika Reinke, Vivienn Weru +352
The number of international benchmarking competitions is steadily increasing in various fields of machine learning (ML) research and practice. So far, however, little is known abou…
Motion-resolved fat-fraction mapping with whole-heart free-running multiecho gre and pilot tone
Adèle L. C. Mackowiak, Christopher W. Roy, Jérôme Yerly +6
PURPOSE To develop free-running multi-echo GRE for cardiac- and respiratory-motion-resolved whole-heart fat fraction quantification. METHODS Multi-echo readouts optimized for water…