Colonoscopy polyp detection and classification: Dataset creation and comparative evaluations.
Colonoscopy polyp detection and classification: Dataset creation and comparative evaluations.
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结肠镜检查息肉检测和分类：数据集创建和比较评估。
DOI：
10.1371/journal.pone.0255809
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发表时间：
2021
期刊：
影响因子：
3.7
通讯作者：
Wang G
中科院分区：
文献类型：
--
作者：
Li K;Fathan MI;Patel K;Zhang T;Zhong C;Bansal A;Rastogi A;Wang JS;Wang G
结直肠癌（CRC）是最常见的癌症类型之一，具有高死亡率。结肠镜检查是CRC筛查的首选方法，已被证明可有效降低CRC死亡率。因此，可靠的计算机辅助息肉检测和分类系统可以显着提高结肠镜检查的有效性。在本文中，我们创建了一个从各种来源收集的内窥镜数据集，并在经验丰富的胃肠病学家的帮助下注释了息肉位置和分类结果的真实情况。该数据集可以作为一个基准平台来训练和评估息肉分类的机器学习模型。我们还比较了八种最先进的基于深度学习的对象检测模型的性能。结果表明，深度CNN模型在CRC筛选中很有前途。这项工作可以作为息肉检测和分类的未来研究的基线。
Colorectal cancer (CRC) is one of the most common types of cancer with a high mortality rate. Colonoscopy is the preferred procedure for CRC screening and has proven to be effective in reducing CRC mortality. Thus, a reliable computer-aided polyp detection and classification system can significantly increase the effectiveness of colonoscopy. In this paper, we create an endoscopic dataset collected from various sources and annotate the ground truth of polyp location and classification results with the help of experienced gastroenterologists. The dataset can serve as a benchmark platform to train and evaluate the machine learning models for polyp classification. We have also compared the performance of eight state-of-the-art deep learning-based object detection models. The results demonstrate that deep CNN models are promising in CRC screening. This work can serve as a baseline for future research in polyp detection and classification.
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影响因子：
64.8
作者：
Iddan, G;Meron, G;Swain, P
通讯作者：
Swain, P
DOI：
10.1056/nejmoa0800996
发表时间：
2008-09-18
期刊：
The New England journal of medicine
影响因子：
--
作者：
Johnson CD;Chen MH;Toledano AY;Heiken JP;Dachman A;Kuo MD;Menias CO;Siewert B;Cheema JI;Obregon RG;Fidler JL;Zimmerman P;Horton KM;Coakley K;Iyer RB;Hara AK;Halvorsen RA Jr;Casola G;Yee J;Herman BA;Burgart LJ;Limburg PJ
通讯作者：
Limburg PJ
影响因子：
14.9
作者：
Hinton, Geoffrey;Deng, Li;Kingsbury, Brian
通讯作者：
Kingsbury, Brian
影响因子：
8
作者：
Bernal, J.;Sanchez, J.;Vilarino, F.
通讯作者：
Vilarino, F.
影响因子：
12.6
作者：
Chan, Michael Y.;Cohen, Hartley;Spiegel, Brennan M. R.
通讯作者：
Spiegel, Brennan M. R.