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Squeeze and multi-context attention for polyp segmentation
Citation Link: https://doi.org/10.15480/882.4813
Publikationstyp
Journal Article
Date Issued
2023-01
Sprache
English
TORE-DOI
Volume
33
Issue
1
Start Page
123
End Page
142
Citation
International Journal of Imaging Systems and Technology 33 (1): 123-142 (2023-01)
Publisher DOI
Scopus ID
Publisher
Wiley
Artificial Intelligence-based Computer Aided Diagnostics (AI-CADx) have been proposed to help physicians in reducing misdetection of polyps in colonoscopy examination. The heterogeneity of a polyp's appearance makes detection challenging for physicians and AI-CADx. Towards building better AI-CADx, we propose an attention module called Squeeze and Multi-Context Attention (SMCA) that re-calibrates a feature map by providing channel and spatial attention by taking into consideration highly activated features and context of the features at multiple receptive fields simultaneously. We test the effectiveness of SMCA by incorporating it into the encoder of five popular segmentation models. We use five public datasets and construct intra-dataset and inter-dataset test sets to evaluate the generalizing capability of models with SMCA. Our intra-dataset evaluation shows that U-Net with SMCA and without SMCA has a precision of 0.86 ± 0.01 and 0.76 ± 0.02 respectively on CVC-ClinicDB. Our inter-dataset evaluation reveals that U-Net with SMCA and without SMCA has a precision of 0.62 ± 0.01 and 0.55 ± 0.09 respectively when trained on Kvasir-SEG and tested on CVC-ColonDB. Similar results are observed using other segmentation models and other public datasets. In conclusion, we demonstrate that incorporating SMCA into the segmentation models leads to an increase in generalizing capability of the segmentation models.
Subjects
attention
attention gate
polyp segmentation
squeeze and excite
squeeze and multi-context
U-Net
DDC Class
600: Technik
620: Ingenieurwissenschaften
Funding(s)
Funding Organisations
Publication version
acceptedVersion
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Int J Imaging Syst Tech - 2022 - Bhattacharya - Squeeze and multi‐context attention for polyp segmentation.pdf
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