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Prompt-Guided Interactive Segmentation of Interstitial Lung Disease in Thoracic CT

Paper recorded by Signals 4 on 2026-08-28 in cs.CV. Abstract reproduced from arXiv; link to the original below.

Published 2026-08-28 on arXiv · recorded by Signals 4 on 2026-08-31

Category: cs.CV · 计算机视觉 · first seen 2026-08-31

Abstract

Accurate segmentation of interstitial lung disease (ILD) patterns is essential for quantitative disease assessment and longitudinal monitoring. However, existing approaches remain limited by relying on dense annotations and producing static predictions that cannot be refined, motivating interactive approaches. While promptable models show promise in interactive segmentation, their adaptation to IL

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#228 most recent of 237 cs.CV papers we have recorded · ↑ newer: LayerRecall: A State-Conditioned Memory Router for Long-Horizon Consis · ↓ older: Lossy Event Compression: From Event Stream Distortion to Task Performa
Cite this page: Prompt-Guided Interactive Segmentation of Interstitial Lung Disease in Thoracic CT: the #228 most recent of 237 cs.CV papers we have recorded (as of 2026-08-28). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/prompt-guided-interactive-segmentation-of-interstitial-lung-disease-in-thoracic-.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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