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VTRL-Med: Progressive Visual Refinement with Topology-Guided Regularization for Medical Image Clustering

Paper recorded by Signals 4 on 2026-10-23 in cs.CV. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-23 on arXiv · recorded by Signals 4 on 2026-10-26

Category: cs.CV · 计算机视觉 · first seen 2026-10-26

Abstract

Deep clustering offers a promising approach for analyzing large unlabeled medical image datasets, yet prevailing methods still face two limitations: they may neglect class-agnostic structural priors that capture object boundaries and regions, and they do not explicitly encode topological patterns (e.g., connectivity and holes). These sources of information play distinct and complementary roles: vi

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#163 most recent of 756 cs.CV papers we have recorded · ↑ newer: STROKE: Simple Sparse Structural Occlusions for Black-Box Adversarial · ↓ older: Multimodal Generative AI Assists Comprehensive Echocardiographic Inter
Cite this page: VTRL-Med: Progressive Visual Refinement with Topology-Guided Regularization for Medical Image Clustering: the #163 most recent of 756 cs.CV papers we have recorded (as of 2026-10-23). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/vtrl-med-progressive-visual-refinement-with-topology-guided-regularization-for-m.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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