180 citations · 405 across the 8 of their papers we have counts for
4 papers · 1 filter
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…
Multi-scale fully convolutional neural networks for histopathology image segmentation: from nuclear aberrations to the global tissue architecture
Rüdiger Schmitz, Frederic Madesta, Maximilian Nielsen +3
Histopathologic diagnosis relies on simultaneous integration of information from a broad range of scales, ranging from nuclear aberrations () through…
Skin Lesion Classification Using CNNs with Patch-Based Attention and Diagnosis-Guided Loss Weighting
Nils Gessert, Thilo Sentker, Frederic Madesta +5
Objective: This work addresses two key problems of skin lesion classification. The first problem is the effective use of high-resolution images with pretrained standard architectur…
3d-SMRnet: Achieving a new quality of MPI system matrix recovery by deep learning
Ivo Matteo Baltruschat, Patryk Szwargulski, Florian Griese +3
Magnetic particle imaging (MPI) data is commonly reconstructed using a system matrix acquired in a time-consuming calibration measurement. The calibration approach has the importan…