BKAI-IGH
NeoPolyp-Small
is a public dataset released by
[BKAI Research Center](https://bkai.ai)
,
[Hanoi University of Science and Technology](https://hust.edu.vn)
incorporation with
[Institute of Gastroenterology and Hepatology (IGH), Vietnam](http://igh.ac.vn/vi/)
.
This dataset contains 1200 images (1000 WLI and 200 FICE images). The training set consists of 1000 images, and the test set consists of 200 images. All polyps are classified into neoplastic or non-neoplastic classes denoted by red and green colors, respectively.
A larger dataset called
NeoPolyp-Large
contains about 7500 images of four different color modes (WLI, BLI, LCI, FICE) with fire-grained annotations. Please check the information
[HERE](https://bkai.ai/research/bkai-igh-neopolyp-small-a-dataset-for-fine-grained-polyp-segmentation/)
for more details.
All the images were collected in
[IGH](http://igh.ac.vn/vi/)
. Annotations (including segmentation and classification) are added and verified by two experienced endoscopists from
[IGH](http://igh.ac.vn/vi/)
.
Acknowledgments
This dataset is collected thanks to
[the project VINIF.2020.DA17](https://bkai.ai/research/development-of-a-real-time-ai-assisted-system-to-detect-colon-polyps-and-identify-lesions-at-high-risk-of-malignancy-during-endoscopy/)
funded by Vingroup Innovation Foundation. We thank
[IGH](http://igh.ac.vn/vi/)
for collecting and annotating the data.
References
If you use this dataset in your work, please consider to cite the following papers:
1. Lan, P.N., An, N.S., Hang, D.V., Long, D.V., Trung, T.Q., Thuy, N.T., Sang, D.V.:
[NeoUnet: Towards accurate colon polyp segmentation and neoplasm detection](https://link.springer.com/chapter/10.1007/978-3-030-90436-4_2)
. In: Proceedings of the 16th International Symposium on Visual Computing (2021)
2. Nguyen Thanh Duc, Nguyen Thi Oanh, Nguyen Thi Thuy, Tran Minh Triet, Dinh Viet Sang.
[ColonFormer: An Efficient Transformer Based Method for Colon Polyp Segmentation](https://ieeexplore.ieee.org/document/9845389)
. IEEE Access, vol. 10, pp. 80575-80586, 2022
3. Nguyen Hoang Thuan, Nguyen Thi Oanh, Nguyen Thi Thuy, Perry Stuart, Dinh Viet Sang (2023).
[RaBiT: An Efficient Transformer using Bidirectional Feature Pyramid Network with Reverse Attention for Colon Polyp Segmentation](https://arxiv.org/abs/2307.06420)
. arXiv preprint arXiv:2307.06420.
4. Nguyen Sy An, Phan Ngoc Lan, Dao Viet Hang, Dao Van Long, Tran Quang Trung, Nguyen Thi Thuy, Dinh Viet Sang.
[BlazeNeo: Blazing fast polyp segmentation and neoplasm detection](https://ieeexplore.ieee.org/document/9759450)
. IEEE Access, Vol. 10, 2022.