140 citations · 156 across the 9 of their papers we have counts for
5 papers · 1 filter
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…
Standardized Medical Image Classification across Medical Disciplines
Simone Mayer, Dominik Müller, Frank Kramer
AUCMEDI is a Python-based framework for medical image classification. In this paper, we evaluate the capabilities of AUCMEDI, by applying it to multiple datasets. Datasets were spe…
Perspective on Code Submission and Automated Evaluation Platforms for University Teaching
Florian Auer, Johann Frei, Dominik Müller +1
We present a perspective on platforms for code submission and automated evaluation in the context of university teaching. Due to the COVID-19 pandemic, such platforms have become a…
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…