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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

Profile image for Dominik Müller

Dominik Müller Lecturer

Research Assistant
University of Augsburg

Researcher in Medical Image Analysis with Deep Learning focusing on standardization via frameworks like MIScnn & AUCMEDI.

Profile image for Florian Auer

Florian Auer Lecturer

Research Assistant
University of Augsburg

Researcher on interdisciplinary topics in bioinformatics and medical informatics.