AUCMEDI: a framework for Automated Classification of Medical Images Passed
Monday May 22, 2023 10:00 - 14:00 R15
Lecturers: Dominik Müller, Florian Auer
Track: MIE: Sensors, signals and Imaging Informatics
Separate registration required: https://www.mie2023.org/tutorials
The open-source Python framework AUCMEDI offers a solution to the described challenges. The software package not only offers a library as a 'high-level' API for the standardized construction of modern medical image classification pipelines, but also reproducible installation and direct application via Dockerization and automatic hyperparameter detection. With AUCMEDI, researchers are able to set up a complete as well as easy-to-integrate medical image classification pipeline with just a few lines of code. AUCMEDI is available as a Python package via PyPI ('pip install aucmedi') and as a repository via GitHub with detailed documentation, examples, and bindings to modern DevOps (CI/CD) techniques: https://frankkramer-lab.github.io/aucmedi/
Language
English
Seminar type
On site only
Level of knowledge
Advanced
Conference
MIE
Authors
Dominik Müller, Florian Auer, Frank Kramer
Lecturers
Dominik Müller Lecturer
Research Assistant
University of Augsburg
Researcher in Medical Image Analysis with Deep Learning focusing on standardization via frameworks like MIScnn & AUCMEDI.
Florian Auer Lecturer
Research Assistant
University of Augsburg
Researcher on interdisciplinary topics in bioinformatics and medical informatics.