Abstract
Biobanks have become central structures for the provision of data. Raw data such as whole slide images (WSI) are stored in separate systems (PACS) or in biobank information systems. If segmentation or comparable information is to be exchanged in the context of the compilation of cases for the application of AI systems, the limits of proprietary systems are quickly reached. In order to provide these valuable (meta-) data for the description of biological tissue samples, WSI and analysis results, common standards for data exchange are required. Such standards are not currently available. Ongoing standardization developments, in particular the establishment of DICOM for digital pathology in the field of virtual microscopy, will help to provide some of the missing standards. DICOM alone, however, cannot close the gap due to some of the peculiarities of WSIs and corresponding analysis results. We propose a flexible, modular and expandable storage system - OBDEX (Open Block Data Exchange System), which allows the exchange of meta- and analysis data about tissue blocks, glass slides, WSI and analysis results. OBDEX is based on the FAIR data principles and uses only freely available protocols, standards and software libraries. This facilitates data exchange between institutions and working groups. It supports them in identifying suitable cases and samples for virtual studies and in exchanging relevant metadata. At the same time, OBDEX will offer the possibility to store deep learning models for exchange. A publication of source code, interface descriptions and documentation under a free software license is planned.
The work presented here was funded by the Federal Ministry of Education and Research (BMBF) as part of the “BB-IT-Boost” research project.
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David Clunie is a member of the DICOM committee.
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Acknowledgements
We thank David Clunie for his feedback on the current state of DICOM for digital pathology and his comments on OBDEX ideas. We also thank Tobias Dumke, Pascal Helbig and Nick Zimmermann (HTW University of Applied Sciences Berlin) for implementing the CoPaW ePathology platform and collaborating on the integration of the OBDEX system. Finally, we would like to thank Erkan Colakoglu for his work on adaptations for distributing OBDEX via Docker.
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Lindequist, B., Zerbe, N., Hufnagl, P. (2020). OBDEX – Open Block Data Exchange System. In: Holzinger, A., Goebel, R., Mengel, M., Müller, H. (eds) Artificial Intelligence and Machine Learning for Digital Pathology. Lecture Notes in Computer Science(), vol 12090. Springer, Cham. https://doi.org/10.1007/978-3-030-50402-1_8
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