This repository was created from the following review paper: A. Nogueira-Rodríguez; R. Domínguez-Carbajales; H. López-Fernández; Á. Iglesias; J. Cubiella; F. Fdez-Riverola; M. Reboiro-Jato; D. Glez-Peña (2020) Deep Neural Networks approaches for detecting and classifying colorectal polyps. Neurocomputing.
Please, cite it if you find it useful for your research.
As part of AI4PolypNet, we are involved in a challenge that will be developed at iSMIT (September 2024). In this edition we will focus only on colonoscopy images and, apart from classical polyp detection and segmentation we present an extended version of polyp classification, including the challenging serrated sessile adenoma class. All the information is available here.
This repository collects the most relevant studies applying Deep Learning for Polyp Detection and Classification in Colonoscopy from a technical point of view, focusing on the low-level details for the implementation of the DL models. In first place, each study is categorized in three types: (i) polyp detection and localization (through bounding boxes or binary masks, i.e. segmentation), (ii) polyp classification, and (iii) simultaneous polyp detection and classification (i.e. studies based on the usage of a single model such as YOLO or SSD to performs simultaneous polyp detection and classification). Secondly, a summary of the public datasets available as well as the private datasets used in the studies is provided. The third section focuses on technical aspects such as the Deep Learning architectures, the data augmentation techniques and the libraries and frameworks used. Finally, the fourth section summarizes the performance metrics reported by each study.
Suggestions are welcome, please check the contribution guidelines before submitting a pull request.
Table of Contents:
Study | Date | Endoscopy type | Imaging technology | Localization type | Multiple polyp | Real time |
---|---|---|---|---|---|---|
Tajbakhsh et al. 2014, Tajbakhsh et al. 2015 | Sept. 2014 / Apr. 2015 | Conventional | N/A | Bounding box | No | Yes |
Zhu R. et al. 2015 | Oct. 2015 | Conventional | N/A | Bounding box (16x16 patches) | Yes | No |
Park and Sargent 2016 | March 2016 | Conventional | NBI, WL | Bounding box | No | No |
Yu et al. 2017 | Jan. 2017 | Conventional | NBI, WL | Bounding box | No | No |
Zhang R. et al. 2017 | Jan. 2017 | Conventional | NBI, WL | No | No | No |
Yuan and Meng 2017 | Feb. 2017 | WCE | N/A | No | No | No |
Brandao et al. 2018 | Feb. 2018 | Conventional/WCE | N/A | Binary mask | Yes | No |
Zhang R. et al. 2018 | May 2018 | Conventional | WL | Bounding box | No | No |
Misawa et al. 2018 | June 2018 | Conventional | WL | No | Yes | No |
Zheng Y. et al. 2018 | July 2018 | Conventional | NBI, WL | Bounding box | Yes | Yes |
Shin Y. et al. 2018 | July 2018 | Conventional | WL | Bounding box | Yes | No |
Urban et al. 2018 | Sep. 2018 | Conventional | NBI, WL | Bounding box | No | Yes |
Mohammed et al. 2018, GitHub | Sep. 2018 | Conventional | WL | Binary mask | Yes | Yes |
Wang et al. 2018, Wang et al. 2018 | Oct. 2018 | Conventional | N/A | Binary mask | Yes | Yes |
Qadir et al. 2019 | Apr. 2019 | Conventional | NBI, WL | Bounding box | Yes | No |
Blanes-Vidal et al. 2019 | March 2019 | WCE | N/A | Bounding box | Yes | No |
Zhang X. et al. 2019 | March 2019 | Conventional | N/A | Bounding box | Yes | Yes |
Misawa et al. 2019 | June 2019 | Conventional | N/A | No | Yes | No |
Zhu X. et al. 2019 | June 2019 | Conventional | N/A | No | No | Yes |
Ahmad et al. 2019 | June 2019 | Conventional | WL | Bounding box | Yes | Yes |
Sornapudi et al. 2019 | June 2019 | Conventional/WCE | N/A | Binary mask | Yes | No |
Wittenberg et al. 2019 | Sept. 2019 | Conventional | WL | Binary mask | Yes | No |
Yuan Y. et al. 2019 | Sept. 2019 | WCE | N/A | No | No | No |
Ma Y. et al. 2019 | Oct. 2019 | Conventional | N/A | Bounding box | Yes | No |
Tashk et al. 2019 | Dec. 2019 | Conventional | N/A | Binary mask | No | No |
Jia X. et al. 2020 | Jan. 2020 | Conventional | N/A | Binary mask | Yes | No |
Ma Y. et al. 2020 | May 2020 | Conventional | N/A | Bounding box | Yes | No |
Young Lee J. et al. 2020 | May 2020 | Conventional | N/A | Bounding box | Yes | Yes |
Wang W. et al. 2020 | July 2020 | Conventional | WL | No | No | No |
Li T. et al. 2020 | Oct. 2020 | Conventional | N/A | No | No | No |
Sánchez-Peralta et al. 2020 | Nov. 2020 | Conventional | NBI, WL | Binary mask | No | No |
Podlasek J. et al. 2020 | Dec. 2020 | Conventional | N/A | Bounding box | No | Yes |
Qadir et al. 2021 | Feb. 2021 | Conventional | WL | Bounding box | Yes | Yes |
Xu J. et al. 2021 | Feb. 2021 | Conventional | WL | Bounding box | Yes | Yes |
Misawa et al. 2021 | Apr. 2021 | Conventional | WL | No | Yes | Yes |
Livovsky et al. 2021 | June 2021 | Conventional | N/A | Bounding box | Yes | Yes |
Pacal et al. 2021 | July 2021 | Conventional | WL | Bounding box | Yes | Yes |
Liu et al. 2021 | July 2021 | Conventional | N/A | Bounding box | Yes | Yes |
Nogueira-Rodríguez et al. 2021 | Aug. 2021 | Conventional | NBI, WL | Bounding box | Yes | Yes |
Yoshida et al. 2021 | Aug. 2021 | Conventional | WL, LCI | Bounding box | Yes | Yes |
Ma Y. et al. 2021 | Sep. 2021 | Conventional | WL | Bounding box | Yes | No |
Pacal et al. 2022 | Nov. 2021 | Conventional | WL | Bounding box | Yes | Yes |
Nogueira-Rodríguez et al. 2022 | April 2022 | Conventional | NBI, WL | Bounding box | Yes | Yes |
Nogueira-Rodríguez et al. 2023 | March 2023 | Conventional | NBI, WL | Bounding box | Yes | Yes |
Study | Date | Endoscopy type | Imaging technology | Classes | Real time |
---|---|---|---|---|---|
Ribeiro et al. 2016 | Oct. 2016 | Conventional | WL | Neoplastic vs. Non-neoplastic | No |
Zhang R. et al. 2017 | Jan. 2017 | Conventional | NBI, WL | Adenoma vs. hyperplastic <br/> Resectable vs. non-resectable<br/> Adenoma vs. hyperplastic vs. serrated | No |
Byrne et al. 2017 | Oct. 2017 | Conventional | NBI | Adenoma vs. hyperplastic | Yes |
Komeda et al. 2017 | Dec. 2017 | Conventional | NBI, WL, Chromoendoscopy | Adenoma vs. non-adenoma | No |
Chen et al. 2018 | Feb. 2018 | Conventional | NBI | Neoplastic vs. hyperplastic | No |
Lui et al. 2019 | Apr. 2019 | Conventional | NBI, WL | Endoscopically curable lesions vs. endoscopically incurable lesion | No |
Kandel et al. 2019 | June 2019 | Conventional | N/A | Adenoma vs. hyperplastic vs. serrated (sessile serrated adenoma/traditional serrated adenoma) | No |
Zachariah et al. 2019 | Oct. 2019 | Conventional | NBI, WL | Adenoma vs. serrated | Yes |
Bour et al. 2019 | Dec. 2019 | Conventional | N/A | Paris classification: not dangeours (types Ip, Is, IIa, and IIb) vs. dangerous (type IIc) vs. cancer (type III) | No |
Patino-Barrientos et al. 2020 | Jan. 2020 | Conventional | WL | Kudo's classification: malignant (types I, II, III, and IV) vs. non-malignant (type V) | No |
Cheng Tao Pu et al. 2020 | Feb. 2020 | Conventional | NBI, BLI | Modified Sano's (MS) classification: MS I (Hyperplastic) vs. MS II (Low-grade tubular adenomas) vs. MS |
AI辅助编程,代码自动修复
Trae是一种自适应的集成开发环境(IDE),通过自动化和多元协作改变开发流程。利用Trae,团队能够更快速、精确地编写和部署代码,从而提高编程效率和项目交付速度。Trae具备上下文感知和代码自动完成功能,是提升开发效率的理想工具。
AI小说写作助手,一站式润色、改写、扩写
蛙蛙写作—国内先进的AI写作平台,涵盖小说、学术、社交媒体等多场景。提供续写、改写、润色等功能,助力创作者高效优化写作流程。界面简洁,功能全面,适合各类写作者提升内容品质和工作效率。
全能AI智能助手,随时解答生活与工作的多样问题
问小白,由元石科技研发的AI智能助手,快速准确地解答各种生活和工作问题,包括但不限于搜索、规划和社交互动,帮助用户在日常生活中提高效率,轻松管理个人事务。
实时语音翻译/同声传译工具
Transly是一个多场景的AI大语言模型驱动的同声传译、专业翻译助手,它拥有超精准的音频识别翻译能力,几乎零延迟的使用体验和支持多国语言可以让你带它走遍全球,无论你是留学生、商务人士、韩剧美剧爱好者,还是出国游玩、多国会议、跨国追星等等,都可以满足你所有需要同传的场景需求,线上线下通用,扫除语言障碍,让全世界的语言交流不再有国界。
一键生成PPT和Word,让学习生活更轻松
讯飞智文是一个利用 AI 技术的项目,能够帮助用户生成 PPT 以及各类文档。无论是商业领域的市场分析报告、年度目标制定,还是学生群体的职业生涯规划、实习避坑指南,亦或是活动策划、旅游攻略等内容,它都能提供支持,帮助用户精准表达,轻松呈现各种信息。
深度推理能力全新升级,全面对标OpenAI o1
科大讯飞的星火大模型,支持语言理解、知识问答和文本创作等多功能,适用于多种文件和业务场景,提升办公和日常生活的效率。讯飞星火是一个提供丰富智能服务的平台,涵盖科技资讯、图像创作、写作辅助、编程解答、科研文献解读等功能,能为不同需求的用户提供便捷高效的帮助,助力用户轻松获取信息、解决问题,满足多样化使用场景。
一种基于大语言模型的高效单流解耦语音令牌文本到语音合成模型
Spark-TTS 是一个基于 PyTorch 的开源文本到语音合成项目,由多个知名机构联合参与。该项目提供了高效的 LLM(大语言模型)驱动的语音合成方案,支持语音克隆和语音创建功能,可通过命令行界面(CLI)和 Web UI 两种方式使用。用户可以根据需求调整语音的性别、音高、速度等参数,生成高质量的语音。该项目适用于多种场景,如有声读物制作、智能语音助手开发等。
AI助力,做PPT更简单!
咔片是一款轻量化在线演示设计工具,借助 AI 技术,实现从内容生成到智能设计的一站式 PPT 制作服务。支持多种文档格式导入生成 PPT,提供海量模板、智能美化、素材替换等功能,适用于销售、教师、学生等各类人群,能高效制作出高品质 PPT,满足不同场景演示需求。
选题、配图、成文,一站式创作,让内容运营更高效
讯飞绘文,一个AI集成平台,支持写作、选题、配图、排版和发布。高效生成适用于各类媒体的定制内容,加速品牌传播,提升内容营销效果。
专业的AI公文写作平台,公文写作神器
AI 材料星,专业的 AI 公文写作辅助平台,为体制内工作人员提供高效的公文写作解决方案。拥有海量公文文库、9 大核心 AI 功能,支持 30 + 文稿类型生成,助力快速完成领导讲话、工作总结、述职报告等材料,提升办公效率,是体制打工人的得力写作神器。