5 citations · 10 across the 3 of their papers we have counts for
3 papers
cs.CV2022
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…
eess.IV2022★ 5 cited
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…
cs.CV2022★ 5 cited
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…