Double-mix pseudo-label framework: enhancing semi-supervised segmentation on category-imbalanced CT volumes
Sign Up to like & getrecommendations! Published in 2025 at "International Journal of Computer Assisted Radiology and Surgery"
DOI: 10.1007/s11548-024-03281-1
Abstract: Deep-learning-based supervised CT segmentation relies on fully and densely labeled data, the labeling process of which is time-consuming. In this study, our proposed method aims to improve segmentation performance on CT volumes with limited annotated… read more here.
Keywords: segmentation; pseudo label; double mix; supervised segmentation ... See more keywords
Weakly Supervised Segmentation of Buildings in Digital Elevation Models
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2022.3177160
Abstract: The lack of quality label data is considered one of the main bottlenecks for training machine and deep learning (DL) models. Weakly supervised learning using incomplete, coarse, or inaccurate data is an alternative strategy to… read more here.
Keywords: supervised segmentation; weakly supervised; models weakly; elevation ... See more keywords
SemiPSCN: Polarization Semantic Constraint Network for Semi-Supervised Segmentation in Large-Scale and Complex-Valued PolSAR Images
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DOI: 10.1109/tgrs.2023.3333431
Abstract: Since polarimetric synthetic aperture radar (PolSAR) terrain segmentation is a dense prediction task, the disadvantage of inadequate labeled samples greatly limits its performance. In this article, we present a semi-supervised segmentation network called SemiPSCN to… read more here.
Keywords: constraint; polsar; supervised segmentation; semi supervised ... See more keywords
ScribFormer: Transformer Makes CNN Work Better for Scribble-Based Medical Image Segmentation
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Transactions on Medical Imaging"
DOI: 10.1109/tmi.2024.3363190
Abstract: Most recent scribble-supervised segmentation methods commonly adopt a CNN framework with an encoder-decoder architecture. Despite its multiple benefits, this framework generally can only capture small-range feature dependency for the convolutional layer with the local receptive… read more here.
Keywords: branch; segmentation; scribble supervised; supervised segmentation ... See more keywords
Semi-supervised segmentation of cardiac chambers from LGE-CMR using feature consistency awareness
Sign Up to like & getrecommendations! Published in 2024 at "BMC Cardiovascular Disorders"
DOI: 10.1186/s12872-024-04250-x
Abstract: Late gadolinium enhancement cardiac magnetic resonance imaging (LGE-CMR) is a valuable cardiovascular imaging technique. Segmentation of cardiac chambers from LGE-CMR is a fundamental step in electrophysiological modeling and cardiovascular disease diagnosis. Deep learning methods have… read more here.
Keywords: lge cmr; segmentation; consistency; cardiac chambers ... See more keywords