-
Article
Open AccessCorrelation of histologic, imaging, and artificial intelligence features in NAFLD patients, derived from Gd-EOB-DTPA-enhanced MRI: a proof-of-concept study
To compare unsupervised deep clustering (UDC) to fat fraction (FF) and relative liver enhancement (RLE) on Gd-EOB-DTPA-enhanced MRI to distinguish simple steatosis from non-alcoholic steatohepatitis (NASH), us...
-
Article
Open AccessDeep learning for predicting future lesion emergence in high-risk breast MRI screening: a feasibility study
International societies have issued guidelines for high-risk breast cancer (BC) screening, recommending contrast-enhanced magnetic resonance imaging (CE-MRI) of the breast as a supplemental diagnostic tool. In...
-
Article
Open AccessEvolution of cortical geometry and its link to function, behaviour and ecology
Studies in comparative neuroanatomy and of the fossil record demonstrate the influence of socio-ecological niches on the morphology of the cerebral cortex, but have led to oftentimes conflicting theories about...
-
Article
Open AccessUnsupervised machine learning identifies predictive progression markers of IPF
To identify and evaluate predictive lung imaging markers and their pathways of change during progression of idiopathic pulmonary fibrosis (IPF) from sequential data of an IPF cohort. To test if these imaging m...
-
Article
Open AccessFetal temporal sulcus depth asymmetry has prognostic value for language development
In most humans, the superior temporal sulcus (STS) shows a rightward depth asymmetry. This asymmetry can not only be observed in adults, but is already recognizable in the fetal brain. As the STS lies adjacent...
-
Article
Open AccessImpact of a content-based image retrieval system on the interpretation of chest CTs of patients with diffuse parenchymal lung disease
Content-based image retrieval systems (CBIRS) are a new and potentially impactful tool for radiological reporting, but their clinical evaluation is largely missing. This study aimed at assessing the effect of ...
-
Article
Open AccessThe Digital Brain Tumour Atlas, an open histopathology resource
Currently, approximately 150 different brain tumour types are defined by the WHO. Recent endeavours to exploit machine learning and deep learning methods for supporting more precise diagnostics based on the hi...
-
Chapter and Conference Paper
Spatio-Temporal Motion Correction and Iterative Reconstruction of In-Utero Fetal fMRI
Resting-state functional Magnetic Resonance Imaging (fMRI) is a powerful imaging technique for studying functional development of the brain in utero. However, unpredictable and excessive movement of fetuses have ...
-
Chapter and Conference Paper
Identifying Phenotypic Concepts Discriminating Molecular Breast Cancer Sub-Types
Molecular breast cancer sub-types derived from core-biopsy are central for individual outcome prediction and treatment decisions. Determining sub-types by non-invasive imaging procedures would benefit early as...
-
Article
Open AccessCorrection to: Radiomics score predicts acute respiratory distress syndrome based on the initial CT scan after trauma
A Correction to this paper has been published: https://doi.org/https://doi.org/10.1007/s00330-021-07995-7
-
Article
Open AccessDynamic memory to alleviate catastrophic forgetting in continual learning with medical imaging
Medical imaging is a central part of clinical diagnosis and treatment guidance. Machine learning has increasingly gained relevance because it captures features of disease and treatment response that are releva...
-
Article
Open AccessRadiomics score predicts acute respiratory distress syndrome based on the initial CT scan after trauma
Acute respiratory distress syndrome (ARDS) constitutes a major factor determining the clinical outcome in polytraumatized patients. Early prediction of ARDS is crucial for timely supportive therapy to reduce m...
-
Article
Fetal MRI-based artificial intelligence in gestational age prediction——a practical solution to an unsolved problem?
-
Article
Open AccessEffect of corpus callosum agenesis on the language network in children and adolescents
The present study is interested in the role of the corpus callosum in the development of the language network. We, therefore, investigated language abilities and the language network using task-based fMRI in t...
-
Chapter and Conference Paper
Continual Active Learning for Efficient Adaptation of Machine Learning Models to Changing Image Acquisition
Imaging in clinical routine is subject to changing scanner protocols, hardware, or policies in a typically heterogeneous set of acquisition hardware. Accuracy and reliability of deep learning models suffer fro...
-
Chapter and Conference Paper
Distributionally Robust Segmentation of Abnormal Fetal Brain 3D MRI
The performance of deep neural networks typically increases with the number of training images. However, not all images have the same importance towards improved performance and robustness. In fetal brain MRI,...
-
Article
Open AccessDistributed changes of the functional connectome in patients with glioblastoma
Glioblastoma might have widespread effects on the neural organization and cognitive function, and even focal lesions may be associated with distributed functional alterations. However, functional changes do no...
-
Article
Open AccessAutomatic lung segmentation in routine imaging is primarily a data diversity problem, not a methodology problem
Automated segmentation of anatomical structures is a crucial step in image analysis. For lung segmentation in computed tomography, a variety of approaches exists, involving sophisticated pipelines trained and ...
-
Article
Open AccessDeep learning detection and quantification of pneumothorax in heterogeneous routine chest computed tomography
Automatically detecting and quantifying pneumothorax on chest computed tomography (CT) may impact clinical decision-making. Machine learning methods published so far struggle with the heterogeneity of technica...
-
Article
Open AccessBrainSpace: a toolbox for the analysis of macroscale gradients in neuroimaging and connectomics datasets
Understanding how cognitive functions emerge from brain structure depends on quantifying how discrete regions are integrated within the broader cortical landscape. Recent work established that macroscale brain...
