Thomas Weikert
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View article: IdentiARAT: Toward Automated Identification of Individual ARAT Items from Wearable Sensors
IdentiARAT: Toward Automated Identification of Individual ARAT Items from Wearable Sensors Open
This study explores the potential of using wrist-worn inertial sensors to automate the labeling of ARAT (Action Research Arm Test) items. While the ARAT is commonly used to assess upper limb motor function, its limitations include subjecti…
View article: The emergence of the fractal bronchial tree
The emergence of the fractal bronchial tree Open
The fractal design of the bronchial tree, as described by the Hess–Murray law, facilitates energy-efficient lung ventilation, yet its developmental origins remain unclear. Here, we quantify the rearrangement of the embryonic bronchial tree…
View article: An automated pipeline for computation and analysis of functional ventilation and perfusion lung MRI with matrix pencil decomposition: TrueLung
An automated pipeline for computation and analysis of functional ventilation and perfusion lung MRI with matrix pencil decomposition: TrueLung Open
Purpose: To introduce and evaluate TrueLung, an automated pipeline for computation and analysis of free-breathing and contrast-agent free pulmonary functional MRI. Material and Methods: time-resolved ultra-fast bSSFP acquisitions are trans…
View article: Machine Learning in Cardiothoracic Radiology - from Medical Data Curation to Clinical Application
Machine Learning in Cardiothoracic Radiology - from Medical Data Curation to Clinical Application Open
The thesis is organized into 8 chapters. Its main theme is the creation and investigation of Machine Learning (ML) algorithms for a broad spectrum of tasks in the field of cardiothoracic radiology. This includes data curation, a fundamenta…
View article: Diagnostic accuracy of automated ACR BI-RADS breast density classification using deep convolutional neural networks
Diagnostic accuracy of automated ACR BI-RADS breast density classification using deep convolutional neural networks Open
Objectives High breast density is a well-known risk factor for breast cancer. This study aimed to develop and adapt two (MLO, CC) deep convolutional neural networks (DCNN) for automatic breast density classification on synthetic 2D tomosyn…
View article: Visual and quantitative assessment of hip implant-related metal artifacts at low field MRI: a phantom study comparing a 0.55-T system with 1.5-T and 3-T systems
Visual and quantitative assessment of hip implant-related metal artifacts at low field MRI: a phantom study comparing a 0.55-T system with 1.5-T and 3-T systems Open
View article: Automated lung cancer assessment on 18F-PET/CT using Retina U-Net and anatomical region segmentation
Automated lung cancer assessment on 18F-PET/CT using Retina U-Net and anatomical region segmentation Open
View article: Natural Language Processing and Graph Theory: Making Sense of Imaging Records in a Novel Representation Frame
Natural Language Processing and Graph Theory: Making Sense of Imaging Records in a Novel Representation Frame Open
Background A concise visualization framework of related reports would increase readability and improve patient management. To this end, temporal referrals to prior comparative exams are an essential connection to previous exams in written …
View article: Correction to: State-of-the-art CT and MR imaging and assessment of atherosclerotic carotid artery disease: the reporting—a consensus document by the European Society of Cardiovascular Radiology (ESCR)
Correction to: State-of-the-art CT and MR imaging and assessment of atherosclerotic carotid artery disease: the reporting—a consensus document by the European Society of Cardiovascular Radiology (ESCR) Open
View article: Correction to: State-of-the-art CT and MR imaging and assessment of atherosclerotic carotid artery disease: standardization of scanning protocols and measurements—a consensus document by the European Society of Cardiovascular Radiology (ESCR)
Correction to: State-of-the-art CT and MR imaging and assessment of atherosclerotic carotid artery disease: standardization of scanning protocols and measurements—a consensus document by the European Society of Cardiovascular Radiology (ESCR) Open
View article: State-of-the-art CT and MR imaging and assessment of atherosclerotic carotid artery disease: standardization of scanning protocols and measurements—a consensus document by the European Society of Cardiovascular Radiology (ESCR)
State-of-the-art CT and MR imaging and assessment of atherosclerotic carotid artery disease: standardization of scanning protocols and measurements—a consensus document by the European Society of Cardiovascular Radiology (ESCR) Open
View article: State-of-the-art CT and MR imaging and assessment of atherosclerotic carotid artery disease: the reporting—a consensus document by the European Society of Cardiovascular Radiology (ESCR)
State-of-the-art CT and MR imaging and assessment of atherosclerotic carotid artery disease: the reporting—a consensus document by the European Society of Cardiovascular Radiology (ESCR) Open
View article: Automated Detection, Segmentation, and Classification of Pericardial Effusions on Chest CT Using a Deep Convolutional Neural Network
Automated Detection, Segmentation, and Classification of Pericardial Effusions on Chest CT Using a Deep Convolutional Neural Network Open
Pericardial effusions (PEFs) are often missed on Computed Tomography (CT), which particularly affects the outcome of patients presenting with hemodynamic compromise. An automatic PEF detection, segmentation, and classification tool would e…
View article: Automated Detection, Segmentation, and Classification of Pleural Effusion From Computed Tomography Scans Using Machine Learning
Automated Detection, Segmentation, and Classification of Pleural Effusion From Computed Tomography Scans Using Machine Learning Open
Objective This study trained and evaluated algorithms to detect, segment, and classify simple and complex pleural effusions on computed tomography (CT) scans. Materials and Methods For detection and segmentation, we randomly selected 160 c…
View article: MRI lung lobe segmentation in pediatric cystic fibrosis patients using a recurrent neural network trained with publicly accessible CT datasets
MRI lung lobe segmentation in pediatric cystic fibrosis patients using a recurrent neural network trained with publicly accessible CT datasets Open
Purpose To introduce a widely applicable workflow for pulmonary lobe segmentation of MR images using a recurrent neural network (RNN) trained with chest CT datasets. The feasibility is demonstrated for 2D coronal ultrafast balanced SSFP (u…
View article: Automated lung vessel segmentation reveals blood vessel volume redistribution in viral pneumonia
Automated lung vessel segmentation reveals blood vessel volume redistribution in viral pneumonia Open
View article: Utilization of Artificial Intelligence–based Intracranial Hemorrhage Detection on Emergent Noncontrast CT Images in Clinical Workflow
Utilization of Artificial Intelligence–based Intracranial Hemorrhage Detection on Emergent Noncontrast CT Images in Clinical Workflow Open
Authors implemented an artificial intelligence (AI)-based detection tool for intracranial hemorrhage (ICH) on noncontrast CT images into an emergent workflow, evaluated its diagnostic performance, and assessed clinical workflow metrics com…
View article: Case Report: Reconstruction of a Large Maxillary Defect With an Engineered, Vascularized, Prefabricated Bone Graft
Case Report: Reconstruction of a Large Maxillary Defect With an Engineered, Vascularized, Prefabricated Bone Graft Open
The reconstruction of complex midface defects is a challenging clinical scenario considering the high anatomical, functional, and aesthetic requirements. In this study, we proposed a surgical treatment to achieve improved oral rehabilitati…
View article: Initial Experience in Developing AI Algorithms in Medical Imaging Based on Annotations Derived From an E-Learning Platform
Initial Experience in Developing AI Algorithms in Medical Imaging Based on Annotations Derived From an E-Learning Platform Open
Development of supervised AI algorithms requires a large amount of labeled images. Image labelling is both time-consuming and expensive. Therefore, we explored the value of e-learning derived annotations for AI algorithm development in med…
View article: MRI lung lobe segmentation in pediatric cystic fibrosis patients using a recurrent neural network trained with publicly accessible CT datasets
MRI lung lobe segmentation in pediatric cystic fibrosis patients using a recurrent neural network trained with publicly accessible CT datasets Open
Purpose: To introduce a widely applicable workflow for pulmonary lobe segmentation of MR images using a recurrent neural network (RNN) trained with chest computed tomography (CT) datasets. The feasibility is demonstrated for 2D coronal ult…
View article: Fully automated guideline-compliant diameter measurements of the thoracic aorta on ECG-gated CT angiography using deep learning
Fully automated guideline-compliant diameter measurements of the thoracic aorta on ECG-gated CT angiography using deep learning Open
The DL-algorithm provided coherent results to radiologists at almost 90% of measurement locations, while the majority of discrepent cases were located at the aortic root. In summary, the DL-algorithm assisted radiologists in performing AHA…
View article: Deep learning-based automated detection of pulmonary embolism on CT pulmonary angiograms: No significant effects on report communication times and patient turnaround in the emergency department nine months after technical implementation
Deep learning-based automated detection of pulmonary embolism on CT pulmonary angiograms: No significant effects on report communication times and patient turnaround in the emergency department nine months after technical implementation Open
View article: Evaluation of liver fibrosis and cirrhosis on the basis of quantitative T1 mapping: Are acute inflammation, age and liver volume confounding factors?
Evaluation of liver fibrosis and cirrhosis on the basis of quantitative T1 mapping: Are acute inflammation, age and liver volume confounding factors? Open
View article: Automated Detection of Pancreatic Cystic Lesions on CT Using Deep Learning
Automated Detection of Pancreatic Cystic Lesions on CT Using Deep Learning Open
Pancreatic cystic lesions (PCL) are a frequent and underreported incidental finding on CT scans and can transform into neoplasms with devastating consequences. We developed and evaluated an algorithm based on a two-step nnU-Net architectur…
View article: Automated CT Lung Density Analysis of Viral Pneumonia and Healthy Lungs Using Deep Learning-Based Segmentation, Histograms and HU Thresholds
Automated CT Lung Density Analysis of Viral Pneumonia and Healthy Lungs Using Deep Learning-Based Segmentation, Histograms and HU Thresholds Open
CT patterns of viral pneumonia are usually only qualitatively described in radiology reports. Artificial intelligence enables automated and reliable segmentation of lungs with chest CT. Based on this, the purpose of this study was to deriv…
View article: Dataset of manually segmented pancreatic cystic lesions in CT images
Dataset of manually segmented pancreatic cystic lesions in CT images Open
This dataset is the data for the paper https://doi.org/10.3390/diagnostics11050901. The dataset contains manual segmentations of pancreatic cysts and main pancreatic ducts in 221 subjects. All images are in Nifti format. Moreover, it conta…
View article: Dataset of manually segmented pancreatic cystic lesions in CT images
Dataset of manually segmented pancreatic cystic lesions in CT images Open
This dataset is the data for the paper https://doi.org/10.3390/diagnostics11050901. The dataset contains manual segmentations of pancreatic cysts and main pancreatic ducts in 221 subjects. All images are in Nifti format. Moreover, it conta…
View article: Building Large-Scale Quantitative Imaging Databases with Multi-Scale Deep Reinforcement Learning: Initial Experience with Whole-Body Organ Volumetric Analyses
Building Large-Scale Quantitative Imaging Databases with Multi-Scale Deep Reinforcement Learning: Initial Experience with Whole-Body Organ Volumetric Analyses Open
To explore the feasibility of a fully automated workflow for whole-body volumetric analyses based on deep reinforcement learning (DRL) and to investigate the influence of contrast-phase (CP) and slice thickness (ST) on the calculated organ…
View article: Prediction of Patient Management in COVID-19 Using Deep Learning-Based Fully Automated Extraction of Cardiothoracic CT Metrics and Laboratory Findings
Prediction of Patient Management in COVID-19 Using Deep Learning-Based Fully Automated Extraction of Cardiothoracic CT Metrics and Laboratory Findings Open
OBJECTIVE: To extract pulmonary and cardiovascular metrics from chest CTs of patients with coronavirus disease 2019 (COVID-19) using a fully automated deep learning-based approach and assess their potential to predict patient management. M…
View article: Lethal COVID-19: Radiologic-Pathologic Correlation of the Lungs
Lethal COVID-19: Radiologic-Pathologic Correlation of the Lungs Open
A significant proportion of GGO correlated with the pathologic processes of diffuse alveolar damage, capillary dilatation and congestion, and microthrombosis. Our results confirm the presence and underline the importance of vascular altera…