Grzegorz Chlebus

Orcid: 0000-0001-6994-696X

According to our database1, Grzegorz Chlebus authored at least 13 papers between 2013 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2023
The Liver Tumor Segmentation Benchmark (LiTS).
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,
Medical Image Anal., 2023

Abstract: Liver Tumor Segmentation in Late-phase MRI using Multi-model Training and an Anisotropic U-Net.
Proceedings of the Bildverarbeitung für die Medizin 2023, 2023

2022
Robust Segmentation Models Using an Uncertainty Slice Sampling-Based Annotation Workflow.
IEEE Access, 2022

Confidence Histograms for Model Reliability Analysis and Temperature Calibration.
Proceedings of the International Conference on Medical Imaging with Deep Learning, 2022

Hepatic artery segmentation with 3D convolutional neural networks.
Proceedings of the Medical Imaging 2022: Computer-Aided Diagnosis, 2022

2021
Anisotropic 3D Multi-Stream CNN for Accurate Prostate Segmentation from Multi-Planar MRI.
Comput. Methods Programs Biomed., 2021

Deep Learning-basierte Oberflächenrekonstruktion aus Binärmasken.
Proceedings of the Bildverarbeitung für die Medizin 2021, 2021

2020
Feasibility of end-to-end trainable two-stage U-Net for detection of axillary lymph nodes in contrast-enhanced CT based on sparse annotations.
Proceedings of the Medical Imaging 2020: Computer-Aided Diagnosis, 2020

2019
The Liver Tumor Segmentation Benchmark (LiTS).
CoRR, 2019

2018
Comparison of U-net-based Convolutional Neural Networks for Liver Segmentation in CT.
CoRR, 2018

2017
Neural Network-Based Automatic Liver Tumor Segmentation With Random Forest-Based Candidate Filtering.
CoRR, 2017

2015
Building Blocks for Clinical Research in Adaptive Radiotherapy.
Proceedings of the 14. Jahrestagung der Deutschen Gesellschaft für Computer- und Roboterassistierte Chirurgie, 2015

2013
Adaptive Confidence Regions of Motion Predictions from Population Exemplar Models.
Proceedings of the Abdominal Imaging. Computation and Clinical Applications, 2013


  Loading...