HEDN: multi-oriented hierarchical extraction and dual-frequency decoupling network for 3D medical image segmentation

Previous 3D encoder-decoder segmentation architectures struggled with fine-grained feature decomposition, resulting in unclear feature hierarchies when fused across layers. Furthermore, the blurred nature of contour boundaries in medical imaging limits the focus on high-frequency contour features. T...

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Vydáno v:	Medical & biological engineering & computing Ročník 63; číslo 1; s. 267 - 291
Hlavní autoři:	Wang, Yu, Huang, Guoheng, Lu, Zeng, Wang, Ying, Chen, Xuhang, Yuan, Xiaochen, Li, Yan, Liu, Jieni, Huang, Yingping
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Berlin/Heidelberg Springer Berlin Heidelberg 01.01.2025 Springer Nature B.V
Témata:	Algorithms Biomedical and Life Sciences Biomedical engineering Biomedical Engineering and Bioengineering Biomedicine Computer Applications Contours data collection Datasets Decoding Decomposition Decoupling Encoders-Decoders Feature decomposition Hierarchies Human Physiology Humans image analysis Image processing Image Processing, Computer-Assisted - methods Image segmentation Imaging Imaging, Three-Dimensional - methods Medical imaging Metric space Modules Neural Networks, Computer Original Article Radiology synapse 3D medical image segmentation Encoder-decoder architecture Dual-frequency decoupling Multi-oriented hierarchical extraction
ISSN:	0140-0118, 1741-0444, 1741-0444
On-line přístup:	Získat plný text
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