arXiv (All)
open access
PET Quantification-Preserving Registration for Longitudinal Whole-Body PSMA PET/CT
We adapt the diffeomorphic coarse-to-fine LapIRN architecture for longitudinal whole-body PSMA PET/CT registration in the Learn2Reg 2026 PSMAReg challenge. The method combines affine pre-registration, multi-modal deformable registration, and test-time instance optimization. We further introduce PET
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
- Non-rigid registration of serial dedicated breast CT, longitudinal dedicated breast CT and PET/CT images using the diffeomorphic demons method#1283474
- Registration is a Representation Problem: Solving Whole-Body PET/CT Registration#1344298
- Registration is a Representation Problem: Solving Whole-Body PET/CT Registration#1319017
- Two-Parameter Flow Map Learning for Continuous-Time Diffeomorphic Image Registration#997779
- A tissue-informed deep learning-based method for positron range correction in preclinical [Formula: see text]Ga PET imaging.#308845
Record · ID 1356787
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