180 citations · 311 across the 29 of their papers we have counts for
19 papers · 1 filter
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…
Skin Lesion Classification Using Ensembles of Multi-Resolution EfficientNets with Meta Data
Nils Gessert, Maximilian Nielsen, Mohsin Shaikh +2
In this paper, we describe our method for the ISIC 2019 Skin Lesion Classification Challenge. The challenge comes with two tasks. For task 1, skin lesions have to be classified bas…
Towards Deep Learning-Based EEG Electrode Detection Using Automatically Generated Labels
Nils Gessert, Martin Gromniak, Marcel Bengs +2
Electroencephalography (EEG) allows for source measurement of electrical brain activity. Particularly for inverse localization, the electrode positions on the scalp need to be know…
Deep Transfer Learning Methods for Colon Cancer Classification in Confocal Laser Microscopy Images
Nils Gessert, Marcel Bengs, Lukas Wittig +4
Purpose: The gold standard for colorectal cancer metastases detection in the peritoneum is histological evaluation of a removed tissue sample. For feedback during interventions, re…