Jens Kleesiek

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A web-based radiomics module for image feature extraction for tumor characterization
MedShapeNet -- A Large-Scale Dataset of 3D Medical Shapes for Computer Vision
GAN-based generation of realistic 3D data: A systematic review and taxonomy
Sparse Convolutional Neural Networks for Medical Image Analysis
Virtual Biopsy: Just an AI Software or a Medical Procedure?
Beyond Medical Imaging-A Review of Multimodal Deep Learning in Radiology
Reference-guided Pseudo-Label Generation for Medical Semantic Segmentation
Vesseg: An Open-Source Tool for Deep Learning-Based Atherosclerotic Plaque Quantification in Histopathology Image.
CT Angiography Clot Burden Score from Data Mining of Structured Reports for Pulmonary Embolism
Discovering Digital Tumor Signatures—Using Latent Code Representations to Manipulate and Classify Liver Lesions
The Federated Tumor Segmentation (FeTS) Challenge
A reporting and analysis framework for structured evaluation of COVID-19 clinical and imaging data
Common Limitations of Image Processing Metrics: A Picture Story
A Relational-learning Perspective to Multi-label Chest X-ray Classification
Adapting Bidirectional Encoder Representations from Transformers (BERT) to Assess Clinical Semantic Textual Similarity: Algorithm Development and Validation Study
Prediction of low-keV monochromatic images from polyenergetic CT scans for improved automatic detection of pulmonary embolism
Ai-based aortic vessel tree segmentation for cardiovascular diseases treatment: status quo
Künstliche Intelligenz in der onkologischen Radiologie: Ein (P)review
MOMO--Deep Learning-driven classification of external DICOM studies for PACS archivation
Joint Imaging Platform for Federated Clinical Data Analytics
Self-Guided Multiple Instance Learning for Weakly Supervised Thoracic DiseaseClassification and Localizationin Chest Radiographs
PSMA PET total tumor volume predicts outcome of patients with advanced prostate cancer receiving [177Lu]Lu-PSMA-617 radioligand therapy in a bicentric analysis
Semi-automatically quantified tumor volume using Ga-68-PSMA-11-PET as biomarker for survival in patients with advanced prostate cancer
Künstliche Intelligenz in der Hybridbildgebung
Analysis of PSMA expression and outcome in patients with advanced Prostate Cancer receiving $^textrm177$ Lu-PSMA-617 Radioligand Therapy
Wie funktioniert maschinelles Lernen?
Wie funktioniert Radiomics?
Künstliche Intelligenz und maschinelles Lernen in der onkologischen Bildgebung
Can Virtual Contrast Enhancement in Brain MRI Replace Gadolinium?: A Feasibility Study