Timo Kepp

Orcid: 0000-0003-2024-2958

According to our database1, Timo Kepp authored at least 20 papers between 2014 and 2024.

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

Timeline

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PhD thesis 
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Links

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Bibliography

2024
Abstract: Reducing Domain Shift in Deep Learning for OCT Segmentation using Image Manipulations.
Proceedings of the Bildverarbeitung für die Medizin 2024, 2024

Abstract: Denoising of Home OCT Images using Noise-to-noise Trained on Artificial Eye Data.
Proceedings of the Bildverarbeitung für die Medizin 2024, 2024

2023
Overcoming the sensor delta for semantic segmentation in OCT images.
Proceedings of the Medical Imaging 2023: Computer-Aided Diagnosis, 2023

Shape-based segmentation of retinal layers and fluids in OCT image data.
Proceedings of the Medical Imaging 2023: Computer-Aided Diagnosis, 2023

Abstract: Shape-based Segmentation of Retinal Layers and Fluids in OCT Image Data.
Proceedings of the Bildverarbeitung für die Medizin 2023, 2023

2022
Analyse anatomischer und pathologischer Strukturen in OCT-Bilddaten mittels maschineller Lernverfahren.
PhD thesis, 2022

Deep learning-based simultaneous registration and unsupervised non-correspondence segmentation of medical images with pathologies.
Int. J. Comput. Assist. Radiol. Surg., 2022

Unsupervised Non-correspondence Detection in Medical Images Using an Image Registration Convolutional Neural Network.
Proceedings of the Biomedical Image Registration - 10th International Workshop, 2022

Epistemic and Aleatoric Uncertainty Estimation for PED, Segmentation in Home OCT Images.
Proceedings of the Bildverarbeitung für die Medizin 2022, 2022

Unsupervised Segmentation of Wounds in Optical Coherence Tomography Images Using Invariant Information Clustering.
Proceedings of the Bildverarbeitung für die Medizin 2022, 2022

2020
Segmentation of retinal low-cost optical coherence tomography images using deep learning.
Proceedings of the Medical Imaging 2020: Computer-Aided Diagnosis, 2020

Abstract: Segmentation of Retinal Low-Cost Optical Coherence Tomography Images Using Deep Learning.
Proceedings of the Bildverarbeitung für die Medizin 2020 - Algorithmen - Systeme, 2020

2019
Interpretable explanations of black box classifiers applied on medical images by meaningful perturbations using variational autoencoders.
Proceedings of the Medical Imaging 2019: Image Processing, 2019

Topology-Preserving Shape-Based Regression Of Retinal Layers In Oct Image Data Using Convolutional Neural Networks.
Proceedings of the 16th IEEE International Symposium on Biomedical Imaging, 2019

Abstract: Interpretable Explanations of Black Box Classifiers Applied on Medical Images by Meaningful Perturbations Using Variational Autoencoders.
Proceedings of the Bildverarbeitung für die Medizin 2019 - Algorithmen - Systeme, 2019

2018
Segmentation of subcutaneous fat within mouse skin in 3D OCT image data using random forests.
Proceedings of the Medical Imaging 2018: Image Processing, 2018

Abstract: Random-Forest-basierte Segmentierung der subkutanen Fettschicht der Mäusehaut in 3D-OCT-Bilddaten.
Proceedings of the Bildverarbeitung für die Medizin 2018 - Algorithmen - Systeme, 2018

2017
Registrierung von nicht sichtbaren Laserbehandlungsarealen der Retina in Live-Aufnahmen des Fundus.
Proceedings of the Bildverarbeitung für die Medizin 2017 - Algorithmen - Systeme, 2017

2015
Evaluation verschiedener Ansätze zur 4D-4D-Registrierung kardiologischer MR-Bilddaten.
Proceedings of the Bildverarbeitung für die Medizin 2015, Algorithmen - Systeme, 2015

2014
Joint multi-object registration and segmentation of left and right cardiac ventricles in 4D cine MRI.
Proceedings of the Medical Imaging 2014: Image Processing, 2014


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