1.4k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Radboud University Medical CenterNL11 papers
- Radboud University NijmegenNL11 papers
- RWTH Aachen UniversityDE11 papers
- Charité - Universitätsmedizin BerlinDE7 papers
- University of BremenDE7 papers
- University of LübeckDE7 papers
- German Cancer Research CenterDE6 papers
- Heidelberg UniversityDE6 papers
- Brigham and Women's HospitalUS5 papers
- Harvard UniversityUS5 papers
- University Hospital HeidelbergDE5 papers
- Freie Universität BerlinDE4 papers
44 papers
Slice-Profile-Enabled Phase Distribution Graphs for MRI Simulation
Snawar Hussain, Daniel C. Hoinkiss, Jörn Huber +2
MRI simulation often separates two descriptions that are both essential for realistic sequence analysis: Bloch dynamics for waveform-resolved radiofrequency (RF) excitation, and ph…
Depth to Anatomy: Organ Localization from Depth Images for Automated Patient Table Positioning in Radiology Workflow
Eytan Kats, Kai Geissler, Daniel Mensing +4
In clinical radiology, accurate patient table positioning is essential to align specific internal organs of interest with the scanner imaging isocenter, ensuring image quality and…
meval: A Statistical Toolbox for Fine-Grained Model Performance Analysis
Dishantkumar Sutariya, Eike Petersen
Analyzing machine learning model performance stratified by patient and recording properties is becoming the accepted norm and often yields crucial insights about important model fa…
From Data to Diagnosis: A Large, Comprehensive Bone Marrow Dataset and AI Methods for Childhood Leukemia Prediction
Henning Höfener, Farina Kock, Martina Pontones +9
Leukemia diagnosis primarily relies on manual microscopic analysis of bone marrow morphology supported by additional laboratory parameters, making it complex and time consuming. Wh…
Robust Renal Mass Segmentation on CT: A Validation Study of an AI-Based Framework
Sarah de Boer, Hartmut Häntze, Kiran Vaidhya Venkadesh +9
Renal mass segmentation has important potential to enhance the clinical workflow, especially in settings requiring quantitative assessments. Kidney volume could serve as an importa…
Carotid Artery Plaque Analysis in 3D Based on Distance Encoding in Mesh Representations
Hinrich Rahlfs, Markus Hüllebrand, Sebastian Schmitter +3
Purpose: Enabling a comprehensive and robust assessment of carotid artery plaques in 3D through extraction and visualization of quantitative plaque parameters. These parameters hav…
Learning Wall Segmentation in 3D Vessel Trees using Sparse Annotations
Hinrich Rahlfs, Markus Hüllebrand, Sebastian Schmitter +3
We propose a novel approach that uses sparse annotations from clinical studies to train a 3D segmentation of the carotid artery wall. We use a centerline annotation to sample perpe…
Rethinking Timing Residuals: Advancing PET Detectors with Explicit TOF Corrections
Stephan Naunheim, Luis Lopes de Paiva, Vanessa Nadig +4
PET is a functional imaging method that visualizes metabolic processes. TOF information can be derived from coincident detector signals and incorporated into image reconstruction t…
Tissue Concepts: supervised foundation models in computational pathology
Till Nicke, Jan Raphael Schaefer, Henning Hoefener +4
Due to the increasing workload of pathologists, the need for automation to support diagnostic tasks and quantitative biomarker evaluation is becoming more and more apparent. Founda…
Slicing Through Bias: Explaining Performance Gaps in Medical Image Analysis using Slice Discovery Methods
Vincent Olesen, Nina Weng, Aasa Feragen +1
Machine learning models have achieved high overall accuracy in medical image analysis. However, performance disparities on specific patient groups pose challenges to their clinical…
Applications of artificial intelligence in the analysis of histopathology images of gliomas: a review
Jan-Philipp Redlich, Friedrich Feuerhake, Joachim Weis +9
In recent years, the diagnosis of gliomas has become increasingly complex. Analysis of glioma histopathology images using artificial intelligence (AI) offers new opportunities to s…
Joining Forces for Pathology Diagnostics with AI Assistance: The EMPAIA Initiative
Norman Zerbe, Lars Ole Schwen, Christian Geißler +17
Over the past decade, artificial intelligence (AI) methods in pathology have advanced substantially. However, integration into routine clinical practice has been slow due to numero…
A structured L-BFGS method and its application to inverse problems
Florian Mannel, Hari Om Aggrawal, Jan Modersitzki
Many inverse problems are phrased as optimization problems in which the objective function is the sum of a data-fidelity term and a regularization. Often, the Hessian of the fideli…
Digitization of Pathology Labs: A Review of Lessons Learned
Lars Ole Schwen, Tim-Rasmus Kiehl, Rita Carvalho +2
Pathology laboratories are increasingly using digital workflows. This has the potential of increasing lab efficiency, but the digitization process also involves major challenges. S…
The NCI Imaging Data Commons as a platform for reproducible research in computational pathology
Daniela P. Schacherer, Markus D. Herrmann, David A. Clunie +7
Background and Objectives: Reproducibility is a major challenge in developing machine learning (ML)-based solutions in computational pathology (CompPath). The NCI Imaging Data Comm…
Understanding metric-related pitfalls in image analysis validation
Annika Reinke, Minu D. Tizabi, Michael Baumgartner +75
Validation metrics are key for the reliable tracking of scientific progress and for bridging the current chasm between artificial intelligence (AI) research and its translation int…
Improving the Timing Resolution of Positron Emission Tomography Detectors Using Boosted Learning -- A Residual Physics Approach
Stephan Naunheim, Yannick Kuhl, David Schug +2
Artificial intelligence (AI) is entering medical imaging, mainly enhancing image reconstruction. Nevertheless, improvements throughout the entire processing, from signal detection…
Anonymization of Whole Slide Images in Histopathology for Research and Education
Tom Bisson, Michael Franz, Isil Dogan O +4
Objective: The exchange of health-related data is subject to regional laws and regulations, such as the General Data Protection Regulation (GDPR) in the EU or the Health Insurance…
Comparison of different automatic solutions for resection cavity segmentation in postoperative MRI volumes including longitudinal acquisitions
Luca Canalini, Jan Klein, Nuno Pedrosa de Barros +3
In this work, we compare five deep learning solutions to automatically segment the resection cavity in postoperative MRI. The proposed methods are based on the same 3D U-Net archit…
Metrics reloaded: Recommendations for image analysis validation
Lena Maier-Hein, Annika Reinke, Patrick Godau +71
Increasing evidence shows that flaws in machine learning (ML) algorithm validation are an underestimated global problem. Particularly in automatic biomedical image analysis, chosen…
Recommendations on test datasets for evaluating AI solutions in pathology
André Homeyer, Christian Geißler, Lars Ole Schwen +27
Artificial intelligence (AI) solutions that automatically extract information from digital histology images have shown great promise for improving pathological diagnosis. Prior to…
A Semi-Monolithic Detector providing intrinsic DOI-encoding and sub-200 ps CRT TOF-Capabilities for Clinical PET Applications
Florian Mueller, Stephan Naunheim, Yannick Kuhl +3
Current clinical PET systems utilize detectors where the scintillator typically contains single elements of 3 - 6 mm width and about 20 mm height. While providing good TOF performa…
Evaluating Generic Auto-ML Tools for Computational Pathology
Lars Ole Schwen, Daniela Schacherer, Christian Geißler +1
Image analysis tasks in computational pathology are commonly solved using convolutional neural networks (CNNs). The selection of a suitable CNN architecture and hyperparameters is…
Responsible and Regulatory Conform Machine Learning for Medicine: A Survey of Challenges and Solutions
Eike Petersen, Yannik Potdevin, Esfandiar Mohammadi +8
Machine learning is expected to fuel significant improvements in medical care. To ensure that fundamental principles such as beneficence, respect for human autonomy, prevention of…