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VascuSR: Iterative Anatomy-Aware Diffusion for CT Super-Resolution

Paper recorded by Signals 4 on 2026-10-14 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-14 on arXiv · recorded by Signals 4 on 2026-10-15

Category: cs.AI · 人工智能 · first seen 2026-10-15

Abstract

Generative super-resolution (SR) can recover sharp detail in computed tomography (CT) images from severely downsampled observations, but the missing high-frequency content is not uniquely determined by the low-resolution input. Consequently, visually plausible reconstructions may contain anatomically unsupported vascular detail, such as missing, spurious, or incorrectly connected vessels. To overc

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#319 most recent of 960 cs.AI papers we have recorded · ↑ newer: VASPO: Self-Distillation with Privileged Value Estimation · ↓ older: Hindsight-Privileged RLVR: Single-Rollout Token Credit Without Group S

Cite this page: VascuSR: Iterative Anatomy-Aware Diffusion for CT Super-Resolution: the #319 most recent of 960 cs.AI papers we have recorded (as of 2026-10-14). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/vascusr-iterative-anatomy-aware-diffusion-for-ct-super-resolution.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json

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