A systematic review on application of deep learning in digestive system image processing
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Graphics and Computer-Aided Design,Computer Vision and Pattern Recognition,Software
Link
https://link.springer.com/content/pdf/10.1007/s00371-021-02322-z.pdf
Reference112 articles.
1. Min, J.K., Kwak, M.S., Cha, J.M.: Overview of deep learning in gastrointestinal endoscopy. Gut Liver. 13(4), 388–393 (2019). https://doi.org/10.5009/gnl18384
2. Tizhoosh, H.R., Pantanowitz, L.: Artificial intelligence and digital pathology: challenges and opportunities. J. Pathol. Inform. (2018). https://doi.org/10.4103/jpi.jpi_53_18
3. Pannala, R., Krishnan, K., Melson, J., Parsi, M.A., Schulman, A.R., Sullivan, S., et al.: Artificial intelligence in gastrointestinal endoscopy. VideoGIE. 5(12), 598–613 (2020). https://doi.org/10.1016/j.vgie.2020.08.013
4. Jisu, H., Bo-Yong, P., Hyunjin, P.: Convolutional neural network classifier for distinguishing Barrett's esophagus and neoplasia endomicroscopy images. Annu Int Conf IEEE Eng Med Biol Soc. 2892–2895 (2017) https://doi.org/10.1109/EMBC.2017.8037461
5. Le Berre, C., Sandborn, W.J., Aridhi, S., Devignes, M., Fournier, L., Smaïl-Tabbone, M., et al.: Application of artificial intelligence to gastroenterology and hepatology. Gastroenterology 158(1), 76–94 (2020). https://doi.org/10.1053/j.gastro.2019.08.058
Cited by 15 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Exploring the benefits and challenges of AI-driven large language models in gastroenterology: Think out of the box;Biomedical Papers;2024-09-04
2. Abnormalities detection from wireless capsule endoscopy images based on embedding learning with triplet loss;Multimedia Tools and Applications;2024-02-12
3. Gastro Intestinal Disease Classification Using Hierarchical Spatio Pyramid TranfoNet With PitTree Fusion and Efficient-CondConv SwishNet;IEEE Access;2024
4. Addressing the data bottleneck in medical deep learning models using a human-in-the-loop machine learning approach;Neural Computing and Applications;2023-11-21
5. Annotate and retrieve in vivo images using hybrid self-organizing map;The Visual Computer;2023-10-31
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3