Image detection method for multi-category lesions in wireless capsule endoscopy based on deep learning models

doi:10.3748/wjg.v30.i48.5111

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Dec 28, 2024 (publication date) through Dec 2, 2024

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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. Dec 28, 2024; 30(48): 5111-5129
Published online Dec 28, 2024. doi: 10.3748/wjg.v30.i48.5111

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Figure 3 Wireless capsule endoscopy_Detection network structure diagram. C1, C2, C3, C4, C5: Layers 1, 2, 3, 4, and 5 of the backbone network; F2, F3, F4, F5: Layers 2, 3, 4, and 5 of the neck network; P2, P3, P4, P5: 2^nd, 3^rd, 4^th, 5^th detection head.

Citation: Xiao ZG, Chen XQ, Zhang D, Li XY, Dai WX, Liang WH. Image detection method for multi-category lesions in wireless capsule endoscopy based on deep learning models. World J Gastroenterol 2024; 30(48): 5111-5129
URL: https://www.wjgnet.com/1007-9327/full/v30/i48/5111.htm
DOI: https://dx.doi.org/10.3748/wjg.v30.i48.5111