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

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.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