45 citations · 88 across the 10 of their papers we have counts for
13 papers
4D Spatio-Temporal Convolutional Networks for Object Position Estimation in OCT Volumes
Marcel Bengs, Nils Gessert, Alexander Schlaefer
Tracking and localizing objects is a central problem in computer-assisted surgery. Optical coherence tomography (OCT) can be employed as an optical tracking system, due to its high…
Spectral-Spatial Recurrent-Convolutional Networks for In-Vivo Hyperspectral Tumor Type Classification
Marcel Bengs, Nils Gessert, Wiebke Laffers +6
Early detection of cancerous tissue is crucial for long-term patient survival. In the head and neck region, a typical diagnostic procedure is an endoscopic intervention where a med…
A Deep Learning Approach for Motion Forecasting Using 4D OCT Data
Marcel Bengs, Nils Gessert, Alexander Schlaefer
Forecasting motion of a specific target object is a common problem for surgical interventions, e.g. for localization of a target region, guidance for surgical interventions, or mot…
4D Deep Learning for Multiple Sclerosis Lesion Activity Segmentation
Nils Gessert, Marcel Bengs, Julia Krüger +5
Multiple sclerosis lesion activity segmentation is the task of detecting new and enlarging lesions that appeared between a baseline and a follow-up brain MRI scan. While deep learn…
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…