6 citations · 23 across the 5 of their papers we have counts for
5 papers
DeepGleason: a System for Automated Gleason Grading of Prostate Cancer using Deep Neural Networks
Dominik Müller, Philip Meyer, Lukas Rentschler +8
Advances in digital pathology and artificial intelligence (AI) offer promising opportunities for clinical decision support and enhancing diagnostic workflows. Previous studies alre…
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…
Towards a Guideline for Evaluation Metrics in Medical Image Segmentation
Dominik Müller, Iñaki Soto-Rey, Frank Kramer
In the last decade, research on artificial intelligence has seen rapid growth with deep learning models, especially in the field of medical image segmentation. Various studies demo…
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…
Assessing the Role of Random Forests in Medical Image Segmentation
Dennis Hartmann, Dominik Müller, Iñaki Soto-Rey +1
Neural networks represent a field of research that can quickly achieve very good results in the field of medical image segmentation using a GPU. A possible way to achieve good resu…