DIY challenge blueprint: from organization to technical realization in biomedical image analysis

  • Biomedical image analysis challenges have become the de facto standard for publishing new datasets and benchmarking different state-of-the-art algorithms. Most challenges use commercial cloud-based platforms, which can limit custom options and involve disadvantages such as reduced data control and increased costs for extended functionalities. In contrast, Do-It-Yourself (DIY) approaches have theBiomedical image analysis challenges have become the de facto standard for publishing new datasets and benchmarking different state-of-the-art algorithms. Most challenges use commercial cloud-based platforms, which can limit custom options and involve disadvantages such as reduced data control and increased costs for extended functionalities. In contrast, Do-It-Yourself (DIY) approaches have the capability to emphasize reliability, compliance, and custom features, providing a solid basis for low-cost, custom designs in self-hosted systems. Our approach emphasizes cost efficiency, improved data sovereignty, and strong compliance with regulatory frameworks, such as the GDPR. This paper presents a blueprint for DIY biomedical imaging challenges, designed to provide institutions with greater autonomy over their challenge infrastructure. Our approach comprehensively addresses both organizational and technical dimensions, including key user roles, data management strategies, and secure, efficient workflows. Key technical contributions include a modular, containerized infrastructure based on Docker, integration of open-source identity management, and automated solution evaluation workflows. Practical deployment guidelines are provided to facilitate implementation and operational stability. The feasibility and adaptability of the proposed framework are demonstrated through the MICCAI 2024 PhaKIR challenge with multiple international teams submitting and validating their solutions through our self-hosted platform. This work can be used as a baseline for future self-hosted DIY implementations and our results encourage further studies in the area of biomedical image analysis challenges.show moreshow less

Export metadata

Additional Services

Share in Twitter Search Google Scholar Statistics
Metadaten
Author:Leonard KlausmannORCiD, Tobias RueckertORCiD, David RauberORCiD, Raphaela MaerklORCiD, Suemeyye R. Yildiran, Max GutbrodORCiD, Christoph PalmORCiD
DOI:https://doi.org/10.1007/978-3-032-05141-7_9
ISBN:978-3-032-05141-7
Parent Title (English):Medical Image Computing and Computer Assisted Intervention - MICCAI 2025 ; Proceedings Part XI
Publisher:Springer
Place of publication:Cham
Document Type:conference proceeding (article)
Language:English
Year of first Publication:2025
Release Date:2025/11/11
Tag:Biomedical challenges; Blueprint; Do-It-Yourself; Image analysis; Self-hosting
First Page:85
Last Page:95
Konferenzangabe:28th International Conference, 23-27 September 2025, Daejeon, South Korea
Andere Schriftenreihe:Lecture Notes in Computer Science, volume 15970
Institutes:Fakultät Informatik und Mathematik
Regensburg Center of Health Sciences and Technology - RCHST
Fakultät Informatik und Mathematik / Labor Regensburg Medical Image Computing (ReMIC)
Begutachtungsstatus:peer-reviewed
research focus:Digitale Transformation
Licence (German):Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG
Einverstanden ✔
Diese Webseite verwendet technisch erforderliche Session-Cookies. Durch die weitere Nutzung der Webseite stimmen Sie diesem zu. Unsere Datenschutzerklärung finden Sie hier.