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Registration is a Representation Problem: Solving Whole-Body PET/CT Registration

Paper recorded by Signals 4 on 2026-10-13 in cs.LG. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-13 on arXiv · recorded by Signals 4 on 2026-10-14

Category: cs.LG · 机器学习 · first seen 2026-10-14

Abstract

Raw image intensities are a poor surrogate for similarity across images in correspondence problems. Further, while auxiliary segmentation labels can provide semantic identification and improve matching, they can assign only coarse identities to fine-grained anatomy and often cover only a subset of structures, particularly in whole-body settings. We present an approach that instead establishes corr

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#294 most recent of 749 cs.LG papers we have recorded · ↑ newer: SkillScaffold: Scaffolding Agentic Reinforcement Learning with Policy- · ↓ older: Emergent Loop Geometry in Gauge-Equivariant Graph Neural Networks
Cite this page: Registration is a Representation Problem: Solving Whole-Body PET/CT Registration: the #294 most recent of 749 cs.LG papers we have recorded (as of 2026-10-13). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/registration-is-a-representation-problem-solving-whole-body-pet-ct-registration.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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