Discriminative Hamiltonian Variational Autoencoder for Accurate Tumor Segmentation in Data-Scarce Regimes

Deep learning has gained significant attention in medical image segmentation. However, the limited availability of annotated training data presents a challenge to achieving accurate results. In efforts to overcome this challenge, data augmentation techniques have been proposed. However, the majority...

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Veröffentlicht in:	arXiv.org
Hauptverfasser:	Aghiles Kebaili, Lapuyade-Lahorgue, Jérôme, Vera, Pierre, Ruan, Su
Format:	Paper
Sprache:	Englisch
Veröffentlicht:	Ithaca Cornell University Library, arXiv.org 17.06.2024
Schlagworte:	Data augmentation Datasets Image processing Image quality Image segmentation Machine learning Masks Medical imaging Positron emission Regularization Target masking
ISSN:	2331-8422
Online-Zugang:	Volltext
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