180 citations · 630 across the 49 of their papers we have counts for
12 papers · 1 filter
Multiple Sclerosis Lesion Activity Segmentation with Attention-Guided Two-Path CNNs
Nils Gessert, Julia Krüger, Roland Opfer +5
Multiple sclerosis is an inflammatory autoimmune demyelinating disease that is characterized by lesions in the central nervous system. Typically, magnetic resonance imaging (MRI) i…
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…
Needle tip force estimation by deep learning from raw spectral OCT data
M. Gromniak, N. Gessert, T. Saathoff +1
Purpose. Needle placement is a challenging problem for applications such as biopsy or brachytherapy. Tip force sensing can provide valuable feedback for needle navigation inside th…
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…