ERCPMP: An Endoscopic Image and Video Dataset for Colorectal Polyps
  Morphology and Pathology
Mojgan Forootan Mohsen Rajabnia Ahmad R Mafi Hamed Azhdari Tehrani Erfan Ghadirzadeh Mahziar Setayeshfar Zahra Ghaffari Mohammad Tashakoripour Mohammad Reza Zali Hamidreza Bolhasani
In the recent years, artificial intelligence (AI) and its leading subtypes,
machine learning (ML) and deep learning (DL) and their applications are
spreading very fast in various aspects such as medicine. Today the most
important challenge of developing accurate algorithms for medical prediction,
detection, diagnosis, treatment and prognosis is data. ERCPMP is an Endoscopic
Image and Video Dataset for Recognition of Colorectal Polyps Morphology and
Pathology. This dataset contains demographic, morphological and pathological
data, endoscopic images and videos of 191 patients with colorectal polyps.
Morphological data is included based on the latest international
gastroenterology classification references such as Paris, Pit and JNET
classification. Pathological data includes the diagnosis of the polyps
including Tubular, Villous, Tubulovillous, Hyperplastic, Serrated, Inflammatory
and Adenocarcinoma with Dysplasia Grade & Differentiation. The current version
of this dataset is published and available on Elsevier Mendeley Dataverse and
since it is under development, the latest version is accessible via:
https://databiox.com.