28 citations · 37 across the 5 of their papers we have counts for
5 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…
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…
Melanoma detection with electrical impedance spectroscopy and dermoscopy using joint deep learning models
Nils Gessert, Marcel Bengs, Alexander Schlaefer
The initial assessment of skin lesions is typically based on dermoscopic images. As this is a difficult and time-consuming task, machine learning methods using dermoscopic images h…