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Anatomy-Decomposed Chest Computed Tomography (CT) Projections as Scalable Supervision for Bone Suppression in Chest Radiographs

Paper recorded by Signals 4 on 2026-09-21 in cs.CV. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-21 on arXiv · recorded by Signals 4 on 2026-09-22

Category: cs.CV · 计算机视觉 · first seen 2026-09-22

Abstract

Bone overlap can obscure abnormalities in chest radiographs, while scarce paired training data limit supervised bone suppression. We address this challenge with a digitally reconstructed radiograph (DRR) framework that converts chest computed tomography (CT) into paired supervision for component suppression. A novel bone segmentation algorithm enables CT decomposition into bone, non-lung soft-tiss

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#3 most recent of 270 cs.CV papers we have recorded · ↑ newer: GAE: Learning a Geometry-Native Latent Space for 3D-Consistent World G · ↓ older: PixelDiT2: Representation-Grounded Pixel Diffusion Transformers
Cite this page: Anatomy-Decomposed Chest Computed Tomography (CT) Projections as Scalable Supervision for Bone Suppression in Chest Radiographs: the #3 most recent of 270 cs.CV papers we have recorded (as of 2026-09-21). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/anatomy-decomposed-chest-computed-tomography-ct-projections-as-scalable-supervis.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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