Jens Kleesiek

Orcid: 0000-0001-8686-0682

Affiliations:
  • University Hospital Essen, Germany


According to our database1, Jens Kleesiek authored at least 172 papers between 2010 and 2025.

Collaborative distances:

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2025
Aortic Vessel Tree Segmentation for Cardiovascular Diseases Treatment: Status Quo.
ACM Comput. Surv., September, 2025

CT-GRAPH: Hierarchical Graph Attention Network for Anatomy-Guided CT Report Generation.
CoRR, August, 2025

GRASPing Anatomy to Improve Pathology Segmentation.
CoRR, August, 2025

Automatic Fine-grained Segmentation-assisted Report Generation.
CoRR, July, 2025

Who Should I Listen To? Adaptive Collaboration in Personalized Federated Learning.
CoRR, July, 2025

Deep Learning-Based Semantic Segmentation for Real-Time Kidney Imaging and Measurements with Augmented Reality-Assisted Ultrasound.
CoRR, June, 2025

Enhancing Privacy: The Utility of Stand-Alone Synthetic CT and MRI for Tumor and Bone Segmentation.
CoRR, June, 2025

From Screen to Space: Evaluating Siemens' Cinematic Reality.
CoRR, June, 2025

Beyond the Desktop: XR-Driven Segmentation with Meta Quest 3 and MX Ink.
CoRR, June, 2025

Good Enough: Is it Worth Improving your Label Quality?
CoRR, May, 2025

PhaseGen: A Diffusion-Based Approach for Complex-Valued MRI Data Generation.
CoRR, April, 2025

Cracking the PUMA Challenge in 24 Hours with CellViT++ and nnU-Net.
CoRR, March, 2025

MeDiSumQA: Patient-Oriented Question-Answer Generation from Discharge Letters.
CoRR, February, 2025

Foreign object segmentation in chest x-rays through anatomy-guided shape insertion.
CoRR, January, 2025

CellViT++: Energy-Efficient and Adaptive Cell Segmentation and Classification Using Foundation Models.
CoRR, January, 2025

Evaluating the effectiveness of biomedical fine-tuning for large language models on clinical tasks.
J. Am. Medical Informatics Assoc., 2025

Real-world federated learning in radiology: hurdles to overcome and benefits to gain.
J. Am. Medical Informatics Assoc., 2025

Why does my medical AI look at pictures of birds? Exploring the efficacy of transfer learning across domain boundaries.
Comput. Methods Programs Biomed., 2025

LIMIS: Towards Language-Based Interactive Medical Image Segmentation.
Proceedings of the 22nd IEEE International Symposium on Biomedical Imaging, 2025

Evaluating Data Augmentation Strategies for Robust Cross-Dataset Generalization in Wound Classification.
Proceedings of the 22nd IEEE International Symposium on Biomedical Imaging, 2025

Abstract: Longitudinal Segmentation of MS Lesions via Temporal Difference Weighting.
Proceedings of the Bildverarbeitung für die Medizin 2025, 2025

Abstract: Skeleton Recall Loss - Connectivity Conserving and Resource Efficient Segmentation of Thin Tubular Structures.
Proceedings of the Bildverarbeitung für die Medizin 2025, 2025

Abstract: Learned Image Compression for HE-stained Histopathological Images via Stain Deconvolution.
Proceedings of the Bildverarbeitung für die Medizin 2025, 2025

Towards Conditioning Clinical Text Generation for User Control.
Proceedings of the Findings of the Association for Computational Linguistics, 2025

A Modular Approach for Clinical SLMs Driven by Synthetic Data with Pre-Instruction Tuning, Model Merging, and Clinical-Tasks Alignment.
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

Every Component Counts: Rethinking the Measure of Success for Medical Semantic Segmentation in Multi-Instance Segmentation Tasks.
Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

Little Is Enough: Boosting Privacy by Sharing Only Hard Labels in Federated Semi-Supervised Learning.
Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

2024
Deep Interactive Segmentation of Medical Images: A Systematic Review and Taxonomy.
IEEE Trans. Pattern Anal. Mach. Intell., December, 2024

Back to the Roots: Reconstructing Large and Complex Cranial Defects using an Image-based Statistical Shape Model.
J. Medical Syst., December, 2024

Model Generalizability Investigation for GFCE-MRI Synthesis in NPC Radiotherapy Using Multi-Institutional Patient-Based Data Normalization.
IEEE J. Biomed. Health Informatics, January, 2024

k-strip: A novel segmentation algorithm in k-space for the application of skull stripping.
Comput. Methods Programs Biomed., January, 2024

CytoNuke Dataset: Towards reliable whole-cell segmentation in bright-field histological images.
Dataset, January, 2024

Privacy-preserving large language models for structured medical information retrieval.
npj Digit. Medicine, 2024

Medical large language models are susceptible to targeted misinformation attacks.
npj Digit. Medicine, 2024

Results from the autoPET challenge on fully automated lesion segmentation in oncologic PET/CT imaging.
Nat. Mac. Intell., 2024

CellViT: Vision Transformers for precise cell segmentation and classification.
Medical Image Anal., 2024

Corrigendum to: GAN-based generation of realistic 3D volumetric data: A systematic review and taxonomy [Medical Image Analysis 93 (2024)].
Medical Image Anal., 2024

GAN-based generation of realistic 3D volumetric data: A systematic review and taxonomy.
Medical Image Anal., 2024

Unlocking the Potential of Digital Pathology: Novel Baselines for Compression.
CoRR, 2024

Improved Multi-Task Brain Tumour Segmentation with Synthetic Data Augmentation.
CoRR, 2024

Brain Tumour Removing and Missing Modality Generation using 3D WDM.
CoRR, 2024

De-Identification of Medical Imaging Data: A Comprehensive Tool for Ensuring Patient Privacy.
CoRR, 2024

Spacewalker: Traversing Representation Spaces for Fast Interactive Exploration and Annotation of Unstructured Data.
CoRR, 2024

Towards Synthetic Data Generation for Improved Pain Recognition in Videos under Patient Constraints.
CoRR, 2024

Data Diet: Can Trimming PET/CT Datasets Enhance Lesion Segmentation?
CoRR, 2024

Autopet III challenge: Incorporating anatomical knowledge into nnUNet for lesion segmentation in PET/CT.
CoRR, 2024

Biomedical Large Languages Models Seem not to be Superior to Generalist Models on Unseen Medical Data.
CoRR, 2024

Tumor likelihood estimation on MRI prostate data by utilizing k-Space information.
CoRR, 2024

A Semi-automatic Cranial Implant Design Tool Based on Rigid ICP Template Alignment and Voxel Space Reconstruction.
CoRR, 2024

CLUE: A Clinical Language Understanding Evaluation for LLMs.
CoRR, 2024

Rethinking Annotator Simulation: Realistic Evaluation of Whole-Body PET Lesion Interactive Segmentation Methods.
CoRR, 2024

How we won BraTS 2023 Adult Glioma challenge? Just faking it! Enhanced Synthetic Data Augmentation and Model Ensemble for brain tumour segmentation.
CoRR, 2024

Deep PCCT: Photon Counting Computed Tomography Deep Learning Applications Review.
CoRR, 2024

Cyto R-CNN and CytoNuke Dataset: Towards reliable whole-cell segmentation in bright-field histological images.
Comput. Methods Programs Biomed., 2024

ChatGPT in healthcare: A taxonomy and systematic review.
Comput. Methods Programs Biomed., 2024

Longitudinal Segmentation of MS Lesions via Temporal Difference Weighting.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024 Workshops, 2024

Comparative Analysis of nnUNet and MedNeXt for Head and Neck Tumor Segmentation in MRI-Guided Radiotherapy.
Proceedings of the Head and Neck Tumor Segmentation for MR-Guided Applications, 2024

Anatomy-Guided Pathology Segmentation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024

Learned Image Compression for HE-Stained Histopathological Images via Stain Deconvolution.
Proceedings of the Medical Optical Imaging and Virtual Microscopy Image Analysis, 2024

Back to the Future: Challenges of Sparse and Irregular Medical Image Time Series.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024 Workshops, 2024

Deep Learning-Based Point Cloud Registration for Augmented Reality-Guided Surgery.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

A Baseline Solution for the ISBI 2024 Dreaming Challenge.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

Enhancing Contrastive Training for Semi-Supervised Chest X-Ray Analysis Through Gaussian Mixture Models.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

Sliding Window Fastedit: A Framework for Lesion Annotation in Whole-Body Pet Images.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

Generalisation of Segmentation Using Generative Adversarial Networks.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

Towards Unifying Anatomy Segmentation: Automated Generation of a Full-Body CT Dataset.
Proceedings of the IEEE International Conference on Image Processing, 2024

Lean Study Host: Towards an Automated Pipeline for Multi-Center Study Hosting.
Proceedings of the 57th Hawaii International Conference on System Sciences, 2024

MultiAR: A Multi-User Augmented Reality Platform for Biomedical Education.
Proceedings of the 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2024

Skeleton Recall Loss for Connectivity Conserving and Resource Efficient Segmentation of Thin Tubular Structures.
Proceedings of the Computer Vision - ECCV 2024, 2024

Taking a Step Back: Revisiting Classical Approaches for Efficient Interactive Segmentation of Medical Images.
Proceedings of the Medical Image Segmentation Foundation Models. CVPR 2024 Challenge: Segment Anything in Medical Images on Laptop, 2024

Filters, Thresholds, and Geodesic Distances for Scribble-Based Interactive Segmentation of Medical Images.
Proceedings of the Medical Image Segmentation Foundation Models. CVPR 2024 Challenge: Segment Anything in Medical Images on Laptop, 2024

Comprehensive Study on German Language Models for Clinical and Biomedical Text Understanding.
Proceedings of the 2024 Joint International Conference on Computational Linguistics, 2024

Accelerating Artificial Intelligence-based Whole Slide Image Analysis with an Optimized Preprocessing Pipeline.
Proceedings of the Bildverarbeitung für die Medizin 2024, 2024

Abstract: Enhanced Diagnostic Fidelity in Pathology Whole Slide Image Compression via Deep Learning.
Proceedings of the Bildverarbeitung für die Medizin 2024, 2024

IKIM at MEDIQA-M3G 2024: Multilingual Visual Question-Answering for Dermatology through VLM Fine-tuning and LLM Translations.
Proceedings of the 6th Clinical Natural Language Processing Workshop, 2024

2023
"A net for everyone": fully personalized and unsupervised neural networks trained with longitudinal data from a single patient.
BMC Medical Imaging, December, 2023



Towards clinical applicability and computational efficiency in automatic cranial implant design: An overview of the AutoImplant 2021 cranial implant design challenge.
Medical Image Anal., August, 2023

Open-source skull reconstruction with MONAI.
SoftwareX, July, 2023

The HoloLens in medicine: A systematic review and taxonomy.
Medical Image Anal., April, 2023

Multimodal extended reality applications offer benefits for volumetric biomedical image analysis in research and medicine.
CoRR, 2023

On the Impact of Cross-Domain Data on German Language Models.
CoRR, 2023

Protecting Sensitive Data through Federated Co-Training.
CoRR, 2023

Medical Foundation Models are Susceptible to Targeted Misinformation Attacks.
CoRR, 2023

Apple Vision Pro for Healthcare: "The Ultimate Display"? - Entering the Wonderland of Precision.
CoRR, 2023

Towards Unifying Anatomy Segmentation: Automated Generation of a Full-body CT Dataset via Knowledge Aggregation and Anatomical Guidelines.
CoRR, 2023

Accurate Fine-Grained Segmentation of Human Anatomy in Radiographs via Volumetric Pseudo-Labeling.
CoRR, 2023

Understanding metric-related pitfalls in image analysis validation.
CoRR, 2023

Valuing vicinity: Memory attention framework for context-based semantic segmentation in histopathology.
Comput. Medical Imaging Graph., 2023

FAM: Relative Flatness Aware Minimization.
Proceedings of the Topological, 2023

Enhanced Diagnostic Fidelity in Pathology Whole Slide Image Compression via Deep Learning.
Proceedings of the Machine Learning in Medical Imaging - 14th International Workshop, 2023

Guiding the Guidance: A Comparative Analysis of User Guidance Signals for Interactive Segmentation of Volumetric Images.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

Anatomy Completor: A Multi-class Completion Framework for 3D Anatomy Reconstruction.
Proceedings of the Shape in Medical Imaging - International Workshop, 2023

Enhanced Data Augmentation Using Synthetic Data for Brain Tumour Segmentation.
Proceedings of the Brain Tumor Segmentation, and Cross-Modality Domain Adaptation for Medical Image Segmentation, 2023

Multimodal Interactive Lung Lesion Segmentation: A Framework for Annotating PET/CT Images Based on Physiological and Anatomical Cues.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

Mirror U-Net: Marrying Multimodal Fission with Multi-task Learning for Semantic Segmentation in Medical Imaging.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

On the Impact of Cross-Domain Data on German Language Models.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Abstract: Deep-learning on Lossily Compressed Pathology Images - Adverse Effects for ImageNet Pre-trained Models.
Proceedings of the Bildverarbeitung für die Medizin 2023, 2023

2022
nipy/nipype: 1.8.3.
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,
Dataset, July, 2022

nipy/nipype: 1.8.1.
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,
Dataset, May, 2022

nipy/nipype: 1.8.0.
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,
Dataset, May, 2022

nipy/nipype: 1.7.1.
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,
Dataset, April, 2022

Current State of Community-Driven Radiological AI Deployment in Medical Imaging.
CoRR, 2022

AutoPET Challenge: Combining nn-Unet with Swin UNETR Augmented by Maximum Intensity Projection Classifier.
CoRR, 2022

GAN-based generation of realistic 3D data: A systematic review and taxonomy.
CoRR, 2022

Metrics reloaded: Pitfalls and recommendations for image analysis validation.
CoRR, 2022

Review of Disentanglement Approaches for Medical Applications - Towards Solving the Gordian Knot of Generative Models in Healthcare.
CoRR, 2022

Medical deep learning - A systematic meta-review.
Comput. Methods Programs Biomed., 2022

Breaking with Fixed Set Pathology Recognition Through Report-Guided Contrastive Training.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

Training β-VAE by Aggregating a Learned Gaussian Posterior with a Decoupled Decoder.
Proceedings of the Medical Applications with Disentanglements - First MICCAI Workshop, 2022

Applying Disentanglement in the Medical Domain: An Introduction for the MAD Workshop.
Proceedings of the Medical Applications with Disentanglements - First MICCAI Workshop, 2022

Deep Learning on Lossily Compressed Pathology Images: Adverse Effects for ImageNet Pre-trained Models.
Proceedings of the Medical Optical Imaging and Virtual Microscopy Image Analysis, 2022

CODEX Meets RACOON - A Concept for Collaborative Documentation of Clinical and Radiological COVID-19 Data.
Proceedings of the German Medical Data Sciences 2022 - Future Medicine: More Precise, More Integrative, More Sustainable! - Proceedings of the Joint Conference of the 67th Annual Meeting of the German Association of Medical Informatics, Biometry, and Epidemiology e.V. (gmds) and the 14th Annual Meeting of the TMF, 2022

Structured Knowledge Graphs for Classifying Unseen Patterns in Radiographs.
Proceedings of the Geometric Deep Learning in Medical Image Analysis, 2022

Detailed Annotations of Chest X-Rays via CT Projection for Report Understanding.
Proceedings of the 33rd British Machine Vision Conference 2022, 2022

DICOM Whole Slide Imaging for Computational Pathology Research in Kaapana and the Joint Imaging Platform.
Proceedings of the Bildverarbeitung für die Medizin 2022, 2022

Reference-Guided Pseudo-Label Generation for Medical Semantic Segmentation.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
nipy/nipype: 1.7.0.
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,
Dataset, October, 2021

A reporting and analysis framework for structured evaluation of COVID-19 clinical and imaging data.
npj Digit. Medicine, 2021

MOMO - Deep Learning-driven classification of external DICOM studies for PACS archivation.
CoRR, 2021

AI-based Aortic Vessel Tree Segmentation for Cardiovascular Diseases Treatment: Status Quo.
CoRR, 2021

The Federated Tumor Segmentation (FeTS) Challenge.
CoRR, 2021

Common Limitations of Image Processing Metrics: A Picture Story.
CoRR, 2021

A Relational-Learning Perspective To Multi-Label Chest X-Ray Classification.
Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, 2021

Prediction of Low-Kev Monochromatic Images From Polyenergetic CT Scans For Improved Automatic Detection of Pulmonary Embolism.
Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, 2021

Abstract: Joint Imaging Platform for Federated Clinical Data Analytics.
Proceedings of the Bildverarbeitung für die Medizin 2021, 2021

2020
nipy/nipype: 1.5.1.
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,
Dataset, September, 2020

nipy/nipype: 1.5.0.
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,
Dataset, June, 2020

nipy/nipype: 1.4.2.
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,
Dataset, February, 2020

nipy/nipype: 1.4.1.
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,
Dataset, January, 2020

Self-guided Multiple Instance Learning for Weakly Supervised Disease Classification and Localization in Chest Radiographs.
Proceedings of the Computer Vision - ACCV 2020 - 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30, 2020

2019
nipy/nipype: 1.4.0.
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,
Dataset, December, 2019

nipy/nipype: 1.3.0.
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,
Dataset, November, 2019

nipy/nipype: 1.3.0-rc1.
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,
Dataset, October, 2019

nipy/nipype: 1.2.2.
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,
Dataset, September, 2019

nipy/nipype: 1.2.2.
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,
Dataset, September, 2019

nipy/nipype: 1.2.3.
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,
Dataset, September, 2019

nipy/nipype: 1.2.1.
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,
Dataset, August, 2019

nipy/nipype: 1.2.0.
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,
Dataset, May, 2019

nipy/nipype: 1.1.9.
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,
Dataset, February, 2019

nipy/nipype: 1.1.8.
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,
Dataset, January, 2019

Efficient Web-Based Review for Automatic Segmentation of Volumetric DICOM Images.
Proceedings of the Bildverarbeitung für die Medizin 2019 - Algorithmen - Systeme, 2019

2018
nipy/nipype: 1.1.7.
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,
Dataset, December, 2018

nipy/nipype: 1.1.6.
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,
Dataset, November, 2018

nipy/nipype: 1.1.5.
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,
Dataset, November, 2018

nipy/nipype: 1.1.4.
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,
Dataset, October, 2018

nipy/nipype: 1.1.3.
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,
Dataset, September, 2018

nipy/nipype: 1.1.2.
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,
Dataset, August, 2018

nipy/nipype: 1.1.1.
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,
Dataset, July, 2018

nipy/nipype: Nipype 1.1.0.
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,
Dataset, July, 2018

nipy/nipype: 1.0.4.
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,
Dataset, May, 2018

nipy/nipype: 1.0.4.
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,
Dataset, May, 2018

nipy/nipype: Nipype 1.0.3.
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,
Dataset, April, 2018

nipy/nipype: 1.0.2.
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,
Dataset, March, 2018

nipy/nipype: 1.0.1.
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,
Dataset, February, 2018

nipy/nipype: Nipype - v1.0.0.
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,
Dataset, January, 2018

2017
nipy/nipype: 0.14.0.
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,
Dataset, November, 2017

nipy/nipype: 0.14.0-rc1.
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,
Dataset, November, 2017

nipy/nipype: 0.14.0-rc1.
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,
Dataset, November, 2017

Nipype: a flexible, lightweight and extensible neuroimaging data processing framework in Python. 0.13.1.
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,
Dataset, May, 2017


2016

DALSA: Domain Adaptation for Supervised Learning From Sparsely Annotated MR Images.
IEEE Trans. Medical Imaging, 2016

Deep MRI brain extraction: A 3D convolutional neural network for skull stripping.
NeuroImage, 2016

2015
Crutchfield Information Metric for Quantifying the Inter-sequence Relationship of Multiparametric MRI Data.
Proceedings of the BIOIMAGING 2015, 2015

Crutchfield Information Metric: A Valid Tool for Quality Control of Multiparametric MRI Data?
Proceedings of the Biomedical Engineering Systems and Technologies, 2015

2012
Action-Driven Perception: Neural Architectures Based On Sensorimotor Principles.
PhD thesis, 2012

Action-Driven Perception for a Humanoid.
Proceedings of the Agents and Artificial Intelligence - 4th International Conference, 2012

What do Objects Feel Like? - Active Perception for a Humanoid Robot.
Proceedings of the ICAART 2012 - Proceedings of the 4th International Conference on Agents and Artificial Intelligence, Volume 1, 2012

2011
Reward-driven learning of sensorimotor laws and visual features.
Proceedings of the 1st International Conference on Development and Learning and on Epigenetic Robotics, 2011

2010
RNA secondary structure prediction using a self-consistent mean field approach.
J. Comput. Chem., 2010


  Loading...