René Werner
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Author Swipe
View article: Fully automated quantification of net water uptake in acute ischemic stroke using only non-contrast CT imaging
Fully automated quantification of net water uptake in acute ischemic stroke using only non-contrast CT imaging Open
Objective Estimating early lesion progression in ischemic stroke is essential for assessing thrombolytic treatment efficacy. While computed tomography perfusion (CTP) and diffusion-weighted imaging (DWI) are commonly used to determine irre…
View article: Toward real-time dose-guided radiation therapy: deformable multileaf collimator tracking using motion-model-derived volumetric images in lung and liver cancer patients
Toward real-time dose-guided radiation therapy: deformable multileaf collimator tracking using motion-model-derived volumetric images in lung and liver cancer patients Open
Objective . Accurate dose delivery in the presence of anatomical motion and deformation remains a major challenge in radiation therapy. Real-time dose-guided radiation therapy addresses this challenge by integrating volumetric imaging, dos…
View article: Fast enrichment and detection of circulating tumor cells from large volumes of whole blood of breast cancer patients utilizing a functionalized bioaffinity <scp>CTC</scp> filtration membrane
Fast enrichment and detection of circulating tumor cells from large volumes of whole blood of breast cancer patients utilizing a functionalized bioaffinity <span>CTC</span> filtration membrane Open
Circulating tumor cells (CTCs) are valuable liquid biopsy analytes as they facilitate an in‐depth characterization of disseminated tumors by a simple blood draw. Most CTC assays can only process limited blood volumes, potentially hampering…
View article: Cluster-based human-in-the-loop strategy for improving machine learning-based circulating tumor cell detection in liquid biopsy
Cluster-based human-in-the-loop strategy for improving machine learning-based circulating tumor cell detection in liquid biopsy Open
In liquid biopsy, detecting and differentiating circulating tumor cells (CTCs) and non-CTCs in metastatic cancer patients' blood samples remains challenging. The current gold standard often involves tedious manual examination of extensive …
View article: Transferable automatic hematological cell classification: Overcoming data limitations with self-supervised learning
Transferable automatic hematological cell classification: Overcoming data limitations with self-supervised learning Open
The results demonstrate that SSL enables (1) extraction of meaningful cell image features without the use of cell class information; (2) efficient transfer of knowledge between bone marrow and peripheral blood cell domains; and (3) efficie…
View article: Oriented histogram-based vector field embedding for characterizing 4D CT data sets in radiotherapy
Oriented histogram-based vector field embedding for characterizing 4D CT data sets in radiotherapy Open
In lung radiotherapy, the primary objective is to optimize treatment outcomes by minimizing exposure to healthy tissues while delivering the prescribed dose to the target volume. The challenge lies in accounting for lung tissue motion due …
View article: Cluster-based human-in-the-loop strategy for improving machine learning-based circulating tumor cell detection in liquid biopsy
Cluster-based human-in-the-loop strategy for improving machine learning-based circulating tumor cell detection in liquid biopsy Open
Detection and differentiation of circulating tumor cells (CTCs) and non-CTCs in blood draws of cancer patients pose multiple challenges. While the gold standard relies on tedious manual evaluation of an automatically generated selection of…
View article: Monte Carlo-based simulation of virtual 3 and 4-dimensional cone-beam computed tomography from computed tomography images: An end-to-end framework and a deep learning-based speedup strategy
Monte Carlo-based simulation of virtual 3 and 4-dimensional cone-beam computed tomography from computed tomography images: An end-to-end framework and a deep learning-based speedup strategy Open
The presented MC pipeline and speedup approach provide an openly accessible end-to-end framework for researchers and clinicians to investigate limitations of image-guided radiation therapy workflows built on both (4D) CT and CBCT images.
View article: Impact of breathing signal‐guided dose modulation on step‐and‐shoot 4D CT image reconstruction
Impact of breathing signal‐guided dose modulation on step‐and‐shoot 4D CT image reconstruction Open
Background Breathing signal‐guided 4D CT sequence scanning such as the intelligent 4D CT (i4DCT) approach reduces imaging artifacts compared to conventional 4D CT. By design, i4DCT captures entire breathing cycles during beam‐on periods, l…
View article: Stability analysis of patient‐specific 4DCT‐ and 4DCBCT‐based correspondence models
Stability analysis of patient‐specific 4DCT‐ and 4DCBCT‐based correspondence models Open
Background Surrogate‐based motion compensation in stereotactic body radiation therapy (SBRT) strongly relies on a constant relationship between an external breathing signal and the internal tumor motion over the course of treatment, that i…
View article: Benchmarking machine learning‐based real‐time respiratory signal predictors in 4D SBRT
Benchmarking machine learning‐based real‐time respiratory signal predictors in 4D SBRT Open
Background Stereotactic body radiotherapy of thoracic and abdominal tumors has to account for respiratory intrafractional tumor motion. Commonly, an external breathing signal is continuously acquired that serves as a surrogate of the tumor…
View article: Time-resolved role of P2X4 and P2X7 during CD8+ T cell activation
Time-resolved role of P2X4 and P2X7 during CD8+ T cell activation Open
CD8 + T cells are a crucial part of the adaptive immune system, responsible for combating intracellular pathogens and tumor cells. The initial activation of T cells involves the formation of highly dynamic Ca 2+ microdomains. Recently, pur…
View article: Spatial normalization for voxel-based lesion symptom mapping: impact of registration approaches
Spatial normalization for voxel-based lesion symptom mapping: impact of registration approaches Open
Background Voxel-based lesion symptom mapping (VLSM) assesses the relation of lesion location at a voxel level with a specific clinical or functional outcome measure at a population level. Spatial normalization, that is, mapping the patien…
View article: DARTS: an open-source Python pipeline for Ca2+ microdomain analysis in live cell imaging data
DARTS: an open-source Python pipeline for Ca2+ microdomain analysis in live cell imaging data Open
Ca 2+ microdomains play a key role in intracellular signaling processes. For instance, they mediate the activation of T cells and, thus, the initial adaptive immune system. They are, however, also of utmost importance for activation of oth…
View article: Deep learning‐based conditional inpainting for restoration of artifact‐affected 4D CT images
Deep learning‐based conditional inpainting for restoration of artifact‐affected 4D CT images Open
Background 4D CT imaging is an essential component of radiotherapy of thoracic and abdominal tumors. 4D CT images are, however, often affected by artifacts that compromise treatment planning quality and image information reliability. Purpo…
View article: Dose reduction in sequence scanning 4D CT imaging through respiratory signal‐guided tube current modulation: A feasibility study
Dose reduction in sequence scanning 4D CT imaging through respiratory signal‐guided tube current modulation: A feasibility study Open
Background Respiratory signal‐guided 4D CT sequence scanning such as the recently introduced Intelligent 4D CT (i4DCT) approach reduces image artifacts compared to conventional 4D CT, especially for irregular breathing. i4DCT selects beam‐…
View article: Self-Supervision for Medical Image Classification: State-of-the-Art Performance with ~100 Labeled Training Samples per Class
Self-Supervision for Medical Image Classification: State-of-the-Art Performance with ~100 Labeled Training Samples per Class Open
Is self-supervised deep learning (DL) for medical image analysis already a serious alternative to the de facto standard of end-to-end trained supervised DL? We tackle this question for medical image classification, with a particular focus …
View article: Adhesion to laminin-1 and collagen IV induces the formation of Ca <sup>2+</sup> microdomains that sensitize mouse T cells for activation
Adhesion to laminin-1 and collagen IV induces the formation of Ca <sup>2+</sup> microdomains that sensitize mouse T cells for activation Open
During an immune response, T cells migrate from blood vessel walls into inflamed tissues by migrating across the endothelium and through extracellular matrix (ECM). Integrins facilitate T cell binding to endothelial cells and ECM proteins.…
View article: Discordant and Converting Receptor Expressions in Brain Metastases from Breast Cancer: MRI-Based Non-Invasive Receptor Status Tracking
Discordant and Converting Receptor Expressions in Brain Metastases from Breast Cancer: MRI-Based Non-Invasive Receptor Status Tracking Open
Discordance and conversion of receptor expressions in metastatic lesions and primary tumors is often observed in patients with brain metastases from breast cancer. Therefore, personalized therapy requires continuous monitoring of receptor …
View article: Intuitive Surgical SurgToolLoc Challenge Results: 2022-2023
Intuitive Surgical SurgToolLoc Challenge Results: 2022-2023 Open
Robotic assisted (RA) surgery promises to transform surgical intervention. Intuitive Surgical is committed to fostering these changes and the machine learning models and algorithms that will enable them. With these goals in mind we have in…
View article: Self-supervision for medical image classification: state-of-the-art performance with ~100 labeled training samples per class
Self-supervision for medical image classification: state-of-the-art performance with ~100 labeled training samples per class Open
Is self-supervised deep learning (DL) for medical image analysis already a serious alternative to the de facto standard of end-to-end trained supervised DL? We tackle this question for medical image classification, with a particular focus …
View article: Clinical application of breathing-adapted 4D CT: image quality comparison to conventional 4D CT
Clinical application of breathing-adapted 4D CT: image quality comparison to conventional 4D CT Open
Purpose: 4D CT imaging is an integral part of 4D radiotherapy workflows. However, 4D CT data often contain motion artifacts that mitigate treatment planning. Recently, breathing-adapted 4D CT (i4DCT) was introduced into clinical practice, …
View article: Dekonvolution von Mikroskopiedaten bei niedrigem Signal-Rausch-Verhältnis
Dekonvolution von Mikroskopiedaten bei niedrigem Signal-Rausch-Verhältnis Open
Fluorescence live cell microscopy is central to the analysis of inter- and intracellular signaling. However, analysis of highly dynamic, local processes requires high temporal and spatial resolution imaging, which is intrinsically linked t…
View article: P94 Deep learning-based automated device detection for assessment standardisation in mechanical thrombectomy
P94 Deep learning-based automated device detection for assessment standardisation in mechanical thrombectomy Open
Introduction Clinical benefits of mechanical thrombectomy (MT) with stent retriever (SR) has shown irrefutable evidence. Post-operative reconstruction of procedural steps is due to lack of conformity in image documentation often challengin…