180 citations · 630 across the 49 of their papers we have counts for
6 papers · 1 filter
Online Strategy Synthesis for Safe and Optimized Control of Steerable Needles
Sascha Lehmann, Antje Rogalla, Maximilian Neidhardt +2
Autonomous systems are often applied in uncertain environments, which require prospective action planning and retrospective data evaluation for future planning to ensure safe opera…
Self-Supervised U-Net for Segmenting Flat and Sessile Polyps
Debayan Bhattacharya, Christian Betz, Dennis Eggert +1
Colorectal Cancer(CRC) poses a great risk to public health. It is the third most common cause of cancer in the US. Development of colorectal polyps is one of the earliest signs of…
A novel optical needle probe for deep learning-based tissue elasticity characterization
Robin Mieling, Johanna Sprenger, Sarah Latus +2
The distinction between malignant and benign tumors is essential to the treatment of cancer. The tissue's elasticity can be used as an indicator for the required tissue characteriz…
Multi-Scale Input Strategies for Medulloblastoma Tumor Classification using Deep Transfer Learning
Marcel Bengs, Satish Pant, Michael Bockmayr +2
Medulloblastoma (MB) is a primary central nervous system tumor and the most common malignant brain cancer among children. Neuropathologists perform microscopic inspection of histop…
3-Dimensional Deep Learning with Spatial Erasing for Unsupervised Anomaly Segmentation in Brain MRI
Marcel Bengs, Finn Behrendt, Julia Krüger +2
Purpose. Brain Magnetic Resonance Images (MRIs) are essential for the diagnosis of neurological diseases. Recently, deep learning methods for unsupervised anomaly detection (UAD) h…
Medulloblastoma Tumor Classification using Deep Transfer Learning with Multi-Scale EfficientNets
Marcel Bengs, Michael Bockmayr, Ulrich Schüller +1
Medulloblastoma (MB) is the most common malignant brain tumor in childhood. The diagnosis is generally based on the microscopic evaluation of histopathological tissue slides. Howev…