180 citations · 581 across the 31 of their papers we have counts for
11 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…
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…
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 Spatio-Temporal Deep Learning with 4D fMRI Data for Autism Spectrum Disorder Classification
Marcel Bengs, Nils Gessert, Alexander Schlaefer
Autism spectrum disorder (ASD) is associated with behavioral and communication problems. Often, functional magnetic resonance imaging (fMRI) is used to detect and characterize brai…
Spatio-spectral deep learning methods for in-vivo hyperspectral laryngeal cancer detection
Marcel Bengs, Stephan Westermann, Nils Gessert +6
Early detection of head and neck tumors is crucial for patient survival. Often, diagnoses are made based on endoscopic examination of the larynx followed by biopsy and histological…
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…
Left Ventricle Quantification Using Direct Regression with Segmentation Regularization and Ensembles of Pretrained 2D and 3D CNNs
Nils Gessert, Alexander Schlaefer
Cardiac left ventricle (LV) quantification provides a tool for diagnosing cardiac diseases. Automatic calculation of all relevant LV indices from cardiac MR images is an intricate…
Spatio-Temporal Deep Learning Models for Tip Force Estimation During Needle Insertion
Nils Gessert, Torben Priegnitz, Thore Saathoff +6
Purpose. Precise placement of needles is a challenge in a number of clinical applications such as brachytherapy or biopsy. Forces acting at the needle cause tissue deformation and…
Efficient Neural Architecture Search on Low-Dimensional Data for OCT Image Segmentation
Nils Gessert, Alexander Schlaefer
Typically, deep learning architectures are handcrafted for their respective learning problem. As an alternative, neural architecture search (NAS) has been proposed where the archit…