Classification of pediatric video capsule endoscopy images for small bowel abnormalities using deep learning models

doi:10.3748/wjg.v31.i21.107601

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Jun 7, 2025 (publication date) through Jun 9, 2025

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World Journal of Gastroenterology

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1007-9327

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Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA

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World J Gastroenterol. Jun 7, 2025; 31(21): 107601
Published online Jun 7, 2025. doi: 10.3748/wjg.v31.i21.107601

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Figure 2 Lesion detection by applying gradient-weighted class activation mapping on representative video capsule endoscopy images, including normal mucosa, erosions/erythema, ulcer, and polyps images. A-D: White-light imaging capsule endoscopic image; E-H: Gradient-weighted class activation mapping image. A and E: Normal mucosa; B and F: Erosions/erythema; C and G: Ulcer; D and H: Polyps. Grad-CAM: Gradient-weighted class activation mapping; VCE: Video capsule endoscopy.

Citation: Huang YH, Lin Q, Jin XY, Chou CY, Wei JJ, Xing J, Guo HM, Liu ZF, Lu Y. Classification of pediatric video capsule endoscopy images for small bowel abnormalities using deep learning models. World J Gastroenterol 2025; 31(21): 107601
URL: https://www.wjgnet.com/1007-9327/full/v31/i21/107601.htm
DOI: https://dx.doi.org/10.3748/wjg.v31.i21.107601