Deutsche Nationalbibliothek
metadata only
Validation of an automated AI-based micro-CT organ segmentation workflow against expert annotations and its impact on fluorescence quantification / Elena Rama, Sihe Yu, Sarah Schraven, Zachary Gurberg, Ekaterina Savina, Jianjun Liu, Zuzanna Anna Magnuska, Felix Gremse, Fabian Kiessling
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Artificial Intelligence Devices for Image Analysis in Digital Pathology#133116
- Artificial Intelligence Devices for Image Analysis in Digital Pathology#131031
- Organoid Intelligent Morphomics: Decoding the organoid morphome through artificial intelligence from phenotypic quantification to mechanistic insight.#928191
- StainX: GPU-accelerated batch stain normalization for computational pathology at scale#657271
- Multi-Granularity Mask-Guided Network: An Integrated AI Framework for Region-Level Segmentation and Grading of Cataract Subtypes on AS-OCT Images.#12774
Record · ID 675406
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive