34 citations · 94 across the 7 of their papers we have counts for
10 papers
Deep learning with 4D spatio-temporal data representations for OCT-based force estimation
Nils Gessert, Marcel Bengs, Matthias Schlüter +1
Estimating the forces acting between instruments and tissue is a challenging problem for robot-assisted minimally-invasive surgery. Recently, numerous vision-based methods have bee…
Deep Learning for High Speed Optical Coherence Elastography
Maximilian Neidhardt, Marcel Bengs, Sarah Latus +3
Mechanical properties of tissue provide valuable information for identifying lesions. One approach to obtain quantitative estimates of elastic properties is shear wave elastography…
Spatio-Temporal Deep Learning Methods for Motion Estimation Using 4D OCT Image Data
Marcel Bengs, Nils Gessert, Matthias Schlüter +1
Purpose. Localizing structures and estimating the motion of a specific target region are common problems for navigation during surgical interventions. Optical coherence tomography…
High-Speed Markerless Tissue Motion Tracking Using Volumetric Optical Coherence Tomography Images
Matthias Schlüter, Lukas Glandorf, Johanna Sprenger +4
Modern optical coherence tomography (OCT) devices provide volumetric images with micrometer-scale spatial resolution and a temporal resolution beyond video rate. In this work, we a…
In-Vitro MPI-Guided IVOCT Catheter Tracking in Real Time for Motion Artifact Compensation
Florian Griese, Sarah Latus, Matthias Schlüter +4
Purpose: Using 4D magnetic particle imaging (MPI), intravascular optical coherence tomography (IVOCT) catheters are tracked in real time in order to compensate for image artifacts…
Bimodal intravascular volumetric imaging combining OCT and MPI
Sarah Latus, Florian Griese, Matthias Schlüter +6
Intravascular optical coherence tomography (IVOCT) is a catheter based image modality allowing for high resolution imaging of vessels. It is based on a fast sequential acquisition…
Towards Automatic Lesion Classification in the Upper Aerodigestive Tract Using OCT and Deep Transfer Learning Methods
Nils Gessert, Matthias Schlüter, Sarah Latus +3
Early detection of cancer is crucial for treatment and overall patient survival. In the upper aerodigestive tract (UADT) the gold standard for identification of malignant tissue is…
Two-path 3D CNNs for calibration of system parameters for OCT-based motion compensation
Nils Gessert, Martin Gromniak, Matthias Schlüter +1
Automatic motion compensation and adjustment of an intraoperative imaging modality's field of view is a common problem during interventions. Optical coherence tomography (OCT) is a…
Feasibility of a markerless tracking system based on optical coherence tomography
Matthias Schlüter, Christoph Otte, Thore Saathoff +2
Clinical tracking systems are popular but typically require specific tracking markers. During the last years, scanning speed of optical coherence tomography (OCT) has increased to…
A Deep Learning Approach for Pose Estimation from Volumetric OCT Data
Nils Gessert, Matthias Schlüter, Alexander Schlaefer
Tracking the pose of instruments is a central problem in image-guided surgery. For microscopic scenarios, optical coherence tomography (OCT) is increasingly used as an imaging moda…