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168,695 papers · 148 categories

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1122 · Jun 202619922001200920172026
2 results for “VarDeepPCA”
Learning a Sampling-Free Variational DNN Plugin from Tiny Training Sets to Refine OOD Segmentation With Uncertainty Estimationcs.CV

VarDeepPCA: A Sampling-Free Variational DNN Plugin for OOD Segmentation with Uncertainty Estimation

problem Deep neural networks (DNNs) fail to generalize to out-of-distribution (OOD) medical images due to variations in scanners and acquisition protocols.
method VarDeepPCA is a lightweight variational DNN framework that learns a distribution of valid anatomical geometries using small in-distribution datasets.
result VarDeepPCA restores segmentation maps produced by existing methods on OOD data to improve anatomical plausibility and reduce errors.
VarDeepPCAOOD segmentationuncertainty estimationgeometric priorssampling-free learning
2026-06-14abs ↗pdf ↗
Learning a Sampling-Free Variational DNN Plugin from Tiny Training Sets to Refine OOD Segmentation With Uncertainty Estimationcs.CV

VarDeepPCA refines medical image segmentation from small datasets, improving anatomical plausibility and reducing errors.

problem Medical image segmentation fails on out-of-distribution data due to variations in scanners and protocols.
method VarDeepPCA learns valid anatomical geometries using only small in-distribution datasets, providing uncertainty estimates.
result VarDeepPCA restores segmentation maps to OOD data, improving anatomical plausibility and reducing errors.
medical image segmentationout-of-distributionvariational learninguncertainty estimationsmall datasets
2026-06-14abs ↗pdf ↗