Conceptio › Archive › arXiv (OAI Expanded)
arXiv (OAI Expanded) open access

Unified CT and MRI Pancreas Segmentation for Label-Efficient Cross-Modality Subregion Transfer

Hong, Ziliang et al.
arXiv (OAI Expanded) · Papers
Open Source ↗Direct PDF ↓
computer-vision-and-pattern-recognition
Robust medical image segmentation across imaging modalities is challenging because of large differences in appearance and intensity distributions. Models trained on a single modality often show substantial performance drops when applied to unseen domains. In this work, we develop a unified 3D pancre
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

Record · ID 1070547
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