An IOMT assisted lung nodule segmentation using enhanced receptive field-based modified UNet
Sign Up to like & getrecommendations! Published in 2021 at "Personal and Ubiquitous Computing"
DOI: 10.1007/s00779-021-01637-x
Abstract: Smart healthcare systems manage and deal with a large amount of data generated by the Internet of Medical Things (IOMT) devices. This big data processing requires efficient computer-aided diagnostic (CAD) systems. Recently, IOMT-based systems are… read more here.
Keywords: modified unet; nodule segmentation; enhanced receptive; lung nodule ... See more keywords
A lung nodule segmentation model based on the transformer with multiple thresholds and coordinate attention
Sign Up to like & getrecommendations! Published in 2024 at "Scientific Reports"
DOI: 10.1038/s41598-024-82877-8
Abstract: Accurate lung nodule segmentation is fundamental for the early detection of lung cancer. With the rapid development of deep learning, lung nodule segmentation models based on the encoder-decoder structure have become the mainstream research approach.… read more here.
Keywords: segmentation model; lung nodule; nodule segmentation; lung ... See more keywords
Improved lung nodule segmentation with a squeeze excitation dilated attention based residual UNet
Sign Up to like & getrecommendations! Published in 2025 at "Scientific Reports"
DOI: 10.1038/s41598-025-85199-5
Abstract: The diverse types and sizes, proximity to non-nodule structures, identical shape characteristics, and varying sizes of nodules make them challenging for segmentation methods. Although many efforts have been made in automatic lung nodule segmentation, most… read more here.
Keywords: squeeze excitation; nodule; segmentation; lung nodule ... See more keywords
Pulmonary Nodule Segmentation Using Deep Learning: A Review
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DOI: 10.1109/access.2024.3447697
Abstract: Accurate segmentation of pulmonary nodule within medical imagery is of great significance for classification and diagnosis. This task is profoundly challenging due to scarcity of annotated data, the diversity of lung nodule features, and the… read more here.
Keywords: segmentation; pulmonary nodule; deep learning; nodule segmentation ... See more keywords
CAFU-Net: A Context-Aware Feature Aggregation Network for Lung Nodule Segmentation
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DOI: 10.1109/access.2025.3555489
Abstract: Accurate segmentation of pulmonary nodules from CT images is of significant importance for the early diagnosis and treatment of lung cancer and related diseases. However, the segmentation task faces challenges due to the overlap between… read more here.
Keywords: lung; segmentation; score; cafu net ... See more keywords
A Level Set Based Unified Framework for Pulmonary Nodule Segmentation
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Signal Processing Letters"
DOI: 10.1109/lsp.2020.3016563
Abstract: This letter introduces a unified framework for accurate segmentation of five different types of pulmonary nodules, namely, solid, juxtapleural, juxtavascular, part solid and ground glass by designing a contrast-adaptive shape-driven level set algorithm. Most of… read more here.
Keywords: nodule segmentation; pulmonary nodule; level set; unified framework ... See more keywords
Ultrasound Nodule Segmentation Using Asymmetric Learning With Simple Clinical Annotation
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Transactions on Circuits and Systems for Video Technology"
DOI: 10.1109/tcsvt.2024.3394261
Abstract: Recent advances in deep learning have greatly facilitated the automated segmentation of ultrasound images, which is essential for nodule morphological analysis. Nevertheless, most existing methods depend on extensive and precise annotations by domain experts, which… read more here.
Keywords: asymmetric learning; segmentation; ultrasound nodule; using asymmetric ... See more keywords