bioRxiv / medRxiv
open access
Mapping multiregional imaging-localized biopsies to MRI habitats reveals biologically significant glioma tissue states and associated patterns of cohabitating cellular subpopulations
Background: Magnetic Resonance Imaging (MRI) is the mainstay for neurosurgical oncology but not for informing us about glioma biology. An obstacle to developing MR-based glioma biomarkers is the absence of rigorous correlation between MRI features and glioma biology as assessed in multi-regional bio
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
- MRI-based brain tumor prediction using convolutional neural network framework.#221076
- A deep learning based NeuroFusionNet approach for automated brain tumor diagnosis from MRI.#150302
- Diffusion-tensor Imaging in Brain Tumors Evaluation#902157
- RegionFM: Interpretable Region-Based Brain MRI Classification Using Foundation Model Embeddings#1319195
- RegionFM: Interpretable Region-Based Brain MRI Classification Using Foundation Model Embeddings#800104
Record · ID 1291912
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