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31 Einträge gefunden

Towards automatic lesion classification in the upper aerodigestive tract using OCT and deep transfer learning methods
2019 - TUHH Open Research
4D spatio-temporal deep learning with 4D fMRI data for autism spectrum disorder classification
2019 - TUHH Open Research - frei zugänglich
Two-path 3D CNNs for calibration of system parameters for OCT-based motion compensation
2019 - TUHH Open Research
Efficient neural architecture search on low-dimensional data for OCT image segmentation
1. Gessert, Nils Thorben
2. Schlaefer, Alexander
2019 - TUHH Open Research - frei zugänglich
Deep Learning in der SPECT und PET des Gehirns
2019 - TUHH Open Research
Feasibility of a markerless tracking system based on optical coherence tomography
2019 - TUHH Open Research
Fully automated lesion segmentation using heavily trained 3D convolutional neural networks are equivalent to manual expert segmentations
2019 - TUHH Open Research
A quantitative metric temporal logic for execution-time constrained verification
2019 - TUHH Open Research
Optimizing robot motion for robotic ultrasound-guided radiation therapy
2019 - TUHH Open Research - frei zugänglich
Bimodal intravascular volumetric imaging combining OCT and MPI
2019 - TUHH Open Research
Feasibility of Colon Cancer Detection in Confocal Laser Microscopy Images Using Convolution Neural Networks
2019 - TUHH Open Research
Spatio-temporal deep learning models for tip force estimation during needle insertion
2019 - TUHH Open Research
Datsets for Publication "In-Vitro MPI-Guided IVOCT Catheter Tracking in Real Time for Motion Artifact Compensation"
2019 - TUHH @ Zenodo - frei zugänglich
Deep transfer learning methods for colon cancer classification in confocal laser microscopy images
2019 - TUHH Open Research
An online model checking approach to soft-tissue detection for rupture
2019 - TUHH Open Research
IVUS-Simulation for Improving Segmentation Performance of Neural Networks via Data Augmentation
2019 - TUHH Open Research
Left Ventricle Quantification Using Direct Regression with Segmentation Regularization and Ensembles of Pretrained 2D and 3D CNNs
1. Gessert, Nils Thorben
2. Schlaefer, Alexander
2019 - TUHH Open Research
Analysis and optimization of the robot setup for robotic-ultrasound-guided radiation therapy
2019 - TUHH Open Research
Machbarkeit CNN-basierter Erzeugung von Kandidatenstrahlen für Radiochirurgie der Prostata
2019 - TUHH Open Research
Towards Deep Learning-Based EEG Electrode Detection Using Automatically Generated Labels
2019 - TUHH Open Research

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Towards automatic lesion classification in the upper aerodigestive tract using OCT and deep transfer learning methods

4D spatio-temporal deep learning with 4D fMRI data for autism spectrum disorder classification

Two-path 3D CNNs for calibration of system parameters for OCT-based motion compensation

Efficient neural architecture search on low-dimensional data for OCT image segmentation

Deep Learning in der SPECT und PET des Gehirns

Feasibility of a markerless tracking system based on optical coherence tomography

Fully automated lesion segmentation using heavily trained 3D convolutional neural networks are equivalent to manual expert segmentations

A quantitative metric temporal logic for execution-time constrained verification

Optimizing robot motion for robotic ultrasound-guided radiation therapy

Bimodal intravascular volumetric imaging combining OCT and MPI

Feasibility of Colon Cancer Detection in Confocal Laser Microscopy Images Using Convolution Neural Networks

Spatio-temporal deep learning models for tip force estimation during needle insertion

Datsets for Publication "In-Vitro MPI-Guided IVOCT Catheter Tracking in Real Time for Motion Artifact Compensation"

Deep transfer learning methods for colon cancer classification in confocal laser microscopy images

An online model checking approach to soft-tissue detection for rupture

IVUS-Simulation for Improving Segmentation Performance of Neural Networks via Data Augmentation

Left Ventricle Quantification Using Direct Regression with Segmentation Regularization and Ensembles of Pretrained 2D and 3D CNNs

Analysis and optimization of the robot setup for robotic-ultrasound-guided radiation therapy

Machbarkeit CNN-basierter Erzeugung von Kandidatenstrahlen für Radiochirurgie der Prostata

Towards Deep Learning-Based EEG Electrode Detection Using Automatically Generated Labels