787 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Graz University of TechnologyAT28 papers
- University of GrazAT20 papers
- BioTechMed-GrazAT19 papers
- Computer Algorithms for MedicineAT6 papers
- Karolinska InstitutetSE5 papers
- Leibniz ScienceCampus Primate CognitionDE5 papers
- Shanghai Jiao Tong UniversityCN5 papers
- University of GöttingenDE5 papers
- Charité - Universitätsmedizin BerlinDE4 papers
- Curtin UniversityAU4 papers
- King's College LondonGB4 papers
- KU LeuvenBE4 papers
17 papers · 1 filter
Semantic-aware Random Convolution and Source Matching for Domain Generalization in Medical Image Segmentation
Franz Thaler, Martin Urschler, Mateusz Kozinski +3
We tackle the challenging problem of single-source domain generalization (DG) for medical image segmentation, where we train a network on one domain (e.g., CT) and directly apply i…
Augmentation-based Domain Generalization and Joint Training from Multiple Source Domains for Whole Heart Segmentation
Franz Thaler, Darko Stern, Gernot Plank +1
As the leading cause of death worldwide, cardiovascular diseases motivate the development of more sophisticated methods to analyze the heart and its substructures from medical imag…
From slides to AI-ready maps: Standardized multi-layer tissue maps as metadata for artificial intelligence in digital pathology
Gernot Fiala, Markus Plass, Robert Harb +15
A Whole Slide Image (WSI) is a high-resolution digital image created by scanning an entire glass slide containing a biological specimen, such as tissue sections or cell samples, at…
Gaussian Process Emulators for Few-Shot Segmentation in Cardiac MRI
Bruno Viti, Franz Thaler, Kathrin Lisa Kapper +3
Segmentation of cardiac magnetic resonance images (MRI) is crucial for the analysis and assessment of cardiac function, helping to diagnose and treat various cardiovascular disease…
Synthetic Augmentation for Anatomical Landmark Localization using DDPMs
Arnela Hadzic, Lea Bogensperger, Simon Johannes Joham +1
Deep learning techniques for anatomical landmark localization (ALL) have shown great success, but their reliance on large annotated datasets remains a problem due to the tedious an…
Comparison of marker-less 2D image-based methods for infant pose estimation
Lennart Jahn, Sarah Flügge, Dajie Zhang +5
In this study we compare the performance of available generic- and infant-pose estimators for a video-based automated general movement assessment (GMA), and the choice of viewing a…
Explainable concept mappings of MRI: Revealing the mechanisms underlying deep learning-based brain disease classification
Christian Tinauer, Anna Damulina, Maximilian Sackl +9
Motivation. While recent studies show high accuracy in the classification of Alzheimer's disease using deep neural networks, the underlying learned concepts have not been investiga…
MedShapeNet -- A Large-Scale Dataset of 3D Medical Shapes for Computer Vision
Jianning Li, Zongwei Zhou, Jiancheng Yang +154
Prior to the deep learning era, shape was commonly used to describe the objects. Nowadays, state-of-the-art (SOTA) algorithms in medical imaging are predominantly diverging from co…
Open video data sharing in developmental and behavioural science
Peter B Marschik, Tomas Kulvicius, Sarah Flügge +10
Video recording is a widely used method for documenting infant and child behaviours in research and clinical practice. Video data has rarely been shared due to ethical concerns of…
Predicting Prostate Cancer-Specific Mortality with A.I.-based Gleason Grading
Ellery Wulczyn, Kunal Nagpal, Matthew Symonds +20
Gleason grading of prostate cancer is an important prognostic factor but suffers from poor reproducibility, particularly among non-subspecialist pathologists. Although artificial i…
A Baseline Approach for AutoImplant: the MICCAI 2020 Cranial Implant Design Challenge
Jianning Li, Antonio Pepe, Christina Gsaxner +2
In this study, we present a baseline approach for AutoImplant (https://autoimplant.grand-challenge.org/) - the cranial implant design challenge, which, as suggested by the organize…
VerSe: A Vertebrae Labelling and Segmentation Benchmark for Multi-detector CT Images
Anjany Sekuboyina, Malek E. Husseini, Amirhossein Bayat +66
Vertebral labelling and segmentation are two fundamental tasks in an automated spine processing pipeline. Reliable and accurate processing of spine images is expected to benefit cl…
Patch augmentation: Towards efficient decision boundaries for neural networks
Marcus D. Bloice, Peter M. Roth, Andreas Holzinger
In this paper we propose a new augmentation technique, called patch augmentation, that, in our experiments, improves model accuracy and makes networks more robust to adversarial at…
Exploit fully automatic low-level segmented PET data for training high-level deep learning algorithms for the corresponding CT data
Christina Gsaxner, Peter M. Roth, Jürgen Wallner +1
We present an approach for fully automatic urinary bladder segmentation in CT images with artificial neural networks in this study. Automatic medical image analysis has become an i…
Computed tomography data collection of the complete human mandible and valid clinical ground truth models
Jürgen Wallner, Irene Mischak, Jan Egger
Image-based algorithmic software segmentation is an increasingly important topic in many medical fields. Algorithmic segmentation is used for medical three-dimensional visualizatio…
Clinical evaluation of semi-automatic opensource algorithmic software segmentation of the mandibular bone: Practical feasibility and assessment of a new course of action
Jürgen Wallner, Kerstin Hochegger, Xiaojun Chen +8
Computer assisted technologies based on algorithmic software segmentation are an increasing topic of interest in complex surgical cases. However - due to functional instability, ti…
Computer-aided position planning of miniplates to treat facial bone defects
Jan Egger, Jürgen Wallner, Markus Gall +4
In this contribution, a software system for computer-aided position planning of miniplates to treat facial bone defects is proposed. The intra-operatively used bone plates have to…