Real-time multi-class detection of colorectal polyps based on the colon-YOLO network
Colorectal adenomatous polyps are key precursors to colorectal cancer (CRC), but their accurate classification during endoscopy remains challenging due to variability in physician expertise and difficulties in detecting certain lesion types, such as sessile serrated adenomas/polyps (SSAP). To addres...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-08-01
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| Series: | Alexandria Engineering Journal |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1110016825006660 |
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| author | Yiliu Liu |
| author_facet | Yiliu Liu |
| author_sort | Yiliu Liu |
| collection | DOAJ |
| description | Colorectal adenomatous polyps are key precursors to colorectal cancer (CRC), but their accurate classification during endoscopy remains challenging due to variability in physician expertise and difficulties in detecting certain lesion types, such as sessile serrated adenomas/polyps (SSAP). To address this, we developed Colon-YOLO, a real-time polyp detection network based on YOLOv5, incorporating ConvNeXt for global feature extraction, a SimAM attention mechanism for enhanced 3D feature weighting, and a concentrated feature pyramid attention layer for improved context capture. A novel Soft-SIoU-NMS method was introduced to boost occlusion detection and convergence speed. Evaluated on both remote and edge devices, the model achieved a 6.3 % mAP improvement (IoU=0.5) over YOLOv5, with inference speeds of 120.5 FPS (remote) and 28.57 FPS (edge), meeting real-time clinical needs. This approach enhances polyp detection accuracy, reducing missed diagnoses and supporting CRC prevention. |
| format | Article |
| id | doaj-art-0ea3a492243746dfa8f84d50bae02afc |
| institution | Kabale University |
| issn | 1110-0168 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Alexandria Engineering Journal |
| spelling | doaj-art-0ea3a492243746dfa8f84d50bae02afc2025-08-22T04:55:30ZengElsevierAlexandria Engineering Journal1110-01682025-08-0112759560510.1016/j.aej.2025.05.045Real-time multi-class detection of colorectal polyps based on the colon-YOLO networkYiliu Liu0China-Japan Union Hospital of Jilin University, 126 Xiantai Street, Changchun 130033, ChinaColorectal adenomatous polyps are key precursors to colorectal cancer (CRC), but their accurate classification during endoscopy remains challenging due to variability in physician expertise and difficulties in detecting certain lesion types, such as sessile serrated adenomas/polyps (SSAP). To address this, we developed Colon-YOLO, a real-time polyp detection network based on YOLOv5, incorporating ConvNeXt for global feature extraction, a SimAM attention mechanism for enhanced 3D feature weighting, and a concentrated feature pyramid attention layer for improved context capture. A novel Soft-SIoU-NMS method was introduced to boost occlusion detection and convergence speed. Evaluated on both remote and edge devices, the model achieved a 6.3 % mAP improvement (IoU=0.5) over YOLOv5, with inference speeds of 120.5 FPS (remote) and 28.57 FPS (edge), meeting real-time clinical needs. This approach enhances polyp detection accuracy, reducing missed diagnoses and supporting CRC prevention.http://www.sciencedirect.com/science/article/pii/S1110016825006660Deep learningColorectal polypsReal-time multi-class detectionEdge deployment |
| spellingShingle | Yiliu Liu Real-time multi-class detection of colorectal polyps based on the colon-YOLO network Alexandria Engineering Journal Deep learning Colorectal polyps Real-time multi-class detection Edge deployment |
| title | Real-time multi-class detection of colorectal polyps based on the colon-YOLO network |
| title_full | Real-time multi-class detection of colorectal polyps based on the colon-YOLO network |
| title_fullStr | Real-time multi-class detection of colorectal polyps based on the colon-YOLO network |
| title_full_unstemmed | Real-time multi-class detection of colorectal polyps based on the colon-YOLO network |
| title_short | Real-time multi-class detection of colorectal polyps based on the colon-YOLO network |
| title_sort | real time multi class detection of colorectal polyps based on the colon yolo network |
| topic | Deep learning Colorectal polyps Real-time multi-class detection Edge deployment |
| url | http://www.sciencedirect.com/science/article/pii/S1110016825006660 |
| work_keys_str_mv | AT yiliuliu realtimemulticlassdetectionofcolorectalpolypsbasedonthecolonyolonetwork |