139 citations · 140 across the 4 of their papers we have counts for
4 papers
Deeply supervised UNet for semantic segmentation to assist dermatopathological assessment of Basal Cell Carcinoma (BCC)
Jean Le'Clerc Arrastia, Nick Heilenkötter, Daniel Otero Baguer +6
Accurate and fast assessment of resection margins is an essential part of a dermatopathologist's clinical routine. In this work, we successfully develop a deep learning method to a…
Deep Relevance Regularization: Interpretable and Robust Tumor Typing of Imaging Mass Spectrometry Data
Christian Etmann, Maximilian Schmidt, Jens Behrmann +6
Neural networks have recently been established as a viable classification method for imaging mass spectrometry data for tumor typing. For multi-laboratory scenarios however, certai…
Peak detection for MALDI mass spectrometry imaging data using sparse frame multipliers
Florian Lieb, Tobias Boskamp, Hans-Georg Stark
MALDI mass spectrometry imaging (MALDI MSI) is a spatially resolved analytical tool for biological tissue analysis by measuring mass-to-charge ratios of ionized molecules. With inc…
Deep Learning for Tumor Classification in Imaging Mass Spectrometry
Jens Behrmann, Christian Etmann, Tobias Boskamp +3
Motivation: Tumor classification using Imaging Mass Spectrometry (IMS) data has a high potential for future applications in pathology. Due to the complexity and size of the data, a…