140 citations · 156 across the 9 of their papers we have counts for
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MISm: A Medical Image Segmentation Metric for Evaluation of weak labeled Data
Dennis Hartmann, Verena Schmid, Philip Meyer +3
Performance measures are an important tool for assessing and comparing different medical image segmentation algorithms. Unfortunately, the current measures have their weaknesses wh…
MISeval: a Metric Library for Medical Image Segmentation Evaluation
Dominik Müller, Dennis Hartmann, Philip Meyer +3
Correct performance assessment is crucial for evaluating modern artificial intelligence algorithms in medicine like deep-learning based medical image segmentation models. However,…
An Analysis on Ensemble Learning optimized Medical Image Classification with Deep Convolutional Neural Networks
Dominik Müller, Iñaki Soto-Rey, Frank Kramer
Novel and high-performance medical image classification pipelines are heavily utilizing ensemble learning strategies. The idea of ensemble learning is to assemble diverse models or…
Classification of Viral Pneumonia X-ray Images with the Aucmedi Framework
Pia Schneider, Dominik Müller, Frank Kramer
In this work we use the AUCMEDI-Framework to train a deep neural network to classify chest X-ray images as either normal or viral pneumonia. Stratified k-fold cross-validation with…