Published July 5, 2023 | Version 1
Dataset Embargoed

DeepHP: A Gastric Mucosa Histopathology Image Collection for Helicobacter pylori Infection Diagnosis

Creators

  • 1. Laboratory of Human and Medical Genetics, Institute of Biological Sciences, Graduate Program of Genetics and Molecular Biology, Federal University of Pará, Belém 66075-110, Brazil
  • 2. Laboratory of Applied Computing, Engineering and Geoscience Institute, Federal University of Western Pará, Santarém 68040-255, Brazil.
  • 3. Research Center on Oncology, Graduate Program of Oncology and Medical Science, Federal University of Pará, Belém 66073-000, Brazil.

Contributors

  • 1. Laboratory of Human and Medical Genetics, Institute of Biological Sciences, Graduate Program of Genetics and Molecular Biology, Federal University of Pará, Belém 66075-110, Brazil

Description

Precision medicine is benefiting from emerging deep learning-based applications, and one such application is computational histopathological analysis. However, a significant challenge arises from the scarcity of properly annotated training image datasets required for generating accurate classification and detection models. This scarcity primarily stems from human-related factors that hinder the acquisition of well-annotated data. To address this issue, the present study introduces DeepHP, a meticulously curated public collection of histopathological images. The DeepHP database encompasses a vast collection of 394,926 histopathological images, out of which 111k were annotated as Helicobacter pylori positive and 283k as Helicobacter pylori-negative.

Notes

The image collection were first described in: Gonçalves, Wanderson Gonçalves e, Marcelo Henrique Paula dos Santos, Leonardo Miranda Brito, Helber Gonzales Almeida Palheta, Fábio Manoel França Lobato, Samia Demachki, Ândrea Ribeiro-dos-Santos, and Gilderlanio Santana de Araújo. 2022. "DeepHP: A New Gastric Mucosa Histopathology Dataset for Helicobacter pylori Infection Diagnosis" International Journal of Molecular Sciences 23, no. 23: 14581. https://doi.org/10.3390/ijms232314581 This research was funded by PROPESP/UFPA for financial support and scholarships, and Fundação Amazônia Paraense de Amparo à Pesquisa—FAPESPA (No. 008/2017 and No. BJT-2021/658671).

Please cite us if you are using our data!

To use DeepHP, the application process includes acceptance of the Data Use Agreement and submission of this online application form to Prof. Dr. Gilderlanio Santana de Araújo (gilderlanio@gmail.com) and Prof. Dr. Ândrea Ribeiro dos Santos (akelyufpa@gmail.com).

 

Files

Embargoed

The files will be made publicly available on December 31, 2030.

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Additional details

References

  • Gonçalves, Wanderson Gonçalves e, Marcelo Henrique Paula dos Santos, Leonardo Miranda Brito, Helber Gonzales Almeida Palheta, Fábio Manoel França Lobato, Samia Demachki, Ândrea Ribeiro-dos-Santos, and Gilderlanio Santana de Araújo. 2022. "DeepHP: A New Gastric Mucosa Histopathology Dataset for Helicobacter pylori Infection Diagnosis" International Journal of Molecular Sciences 23, no. 23: 14581. https://doi.org/10.3390/ijms232314581
  • e Gonçalves, W. G., Dos Santos, M. H. D. P., Lobato, F. M. F., Ribeiro-dos-Santos, Â., & de Araújo, G. S. (2020). Deep learning in gastric tissue diseases: a systematic review. BMJ open gastroenterology, 7(1), e000371.

Subjects

deep learning
01
medical image analysis
02
convolutional neural networks
03