©The Author(s) 2025.
World J Gastroenterol. Nov 7, 2025; 31(41): 111184
Published online Nov 7, 2025. doi: 10.3748/wjg.v31.i41.111184
Published online Nov 7, 2025. doi: 10.3748/wjg.v31.i41.111184
Figure 1 Examples of images with different illumination conditions.
The top row contains images with normal lighting, while the middle row contains images with low lighting, and the bottom row contains images that are partially overexposed.
- Citation: Chan IN, Wong PK, Yan T, Hu YY, Chan CI, Qin YY, Wong CH, Chan IW, Lam IH, Wong SH, Li Z, Gao S, Yu HH, Yao L, Zhao BL, Hu Y. Assessing deep learning models for multi-class upper endoscopic disease segmentation: A comprehensive comparative study. World J Gastroenterol 2025; 31(41): 111184
- URL: https://www.wjgnet.com/1007-9327/full/v31/i41/111184.htm
- DOI: https://dx.doi.org/10.3748/wjg.v31.i41.111184