AWGUNET: Attention-Aided Wavelet Guided U-Net for Nuclei Segmentation in Histopathology Images Article Swipe
Ayush Roy
,
Payel Pramanik
,
Dmitrii Kaplun
,
Sergei A. Antonov
,
Ram Sarkar
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2406.08425
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2406.08425
Accurate nuclei segmentation in histopathological images is crucial for cancer diagnosis. Automating this process offers valuable support to clinical experts, as manual annotation is time-consuming and prone to human errors. However, automating nuclei segmentation presents challenges due to uncertain cell boundaries, intricate staining, and diverse structures. In this paper, we present a segmentation approach that combines the U-Net architecture with a DenseNet-121 backbone, harnessing the strengths of both to capture comprehensive contextual and spatial information. Our model introduces the Wavelet-guided channel attention module to enhance cell boundary delineation, along with a learnable weighted global attention module for channel-specific attention. The decoder module, composed of an upsample block and convolution block, further refines segmentation in handling staining patterns. The experimental results conducted on two publicly accessible histopathology datasets, namely Monuseg and TNBC, underscore the superiority of our proposed model, demonstrating its potential to advance histopathological image analysis and cancer diagnosis. The code is made available at: https://github.com/AyushRoy2001/AWGUNET.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2406.08425
- https://arxiv.org/pdf/2406.08425
- OA Status
- green
- Cited By
- 1
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4399657793
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4399657793Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2406.08425Digital Object Identifier
- Title
-
AWGUNET: Attention-Aided Wavelet Guided U-Net for Nuclei Segmentation in Histopathology ImagesWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-06-12Full publication date if available
- Authors
-
Ayush Roy, Payel Pramanik, Dmitrii Kaplun, Sergei A. Antonov, Ram SarkarList of authors in order
- Landing page
-
https://arxiv.org/abs/2406.08425Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2406.08425Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2406.08425Direct OA link when available
- Concepts
-
Histopathology, Wavelet, Segmentation, Artificial intelligence, Pattern recognition (psychology), Computer science, Computer vision, Medicine, PathologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1Per-year citation counts (last 5 years)
- Related works (count)
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10Other works algorithmically related by OpenAlex
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