ERCPMP: an endoscopic image and video dataset for 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.Objectives: 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 can be used for developing deep learning algorithms for polyps detection, classification, and segmentation.Data description: Images were captured with Olympus colonoscope and are presented in RGB format, JPG type with the resolution of 368 * 256 pixels and 96 dpi. The name of each file (image or video) includes pathological diagnosis, grade and JNet classification of the related polyp.

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Publication Details

Journal
BMC Research Notes
Published
2024-12-28
DOI
https://doi.org/10.1186/s13104-024-07062-6
Citations
3
Primary Topic
Colorectal Cancer Screening and Detection
Type
article
Field-Weighted Citation Impact
0.85
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article

ERCPMP: an endoscopic image and video dataset for colorectal polyps morphology and pathology

Mohammad Reza Zali, Mohammad Tashakoripour, Erfan Ghadirzadeh, Mojgan Forootan et al.
3 citations
BMC Research Notes
Colorectal Cancer Screening and Detection
0.85
article

ERCPMP: an endoscopic image and video dataset for colorectal polyps morphology and pathology

Mohammad Reza Zali, Mohammad Tashakoripour, Erfan Ghadirzadeh, Mojgan Forootan, Hamidreza Bolhasani, Hamed Azhdari Tehrani, Ahmad R Mafi, Zahra Ghaffari, Mohsen Rajabnia, Mahziar Setayeshfar
article en
3 citations

Abstract

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.Objectives: 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 can be used for developing deep learning algorithms for polyps detection, classification, and segmentation.Data description: Images were captured with Olympus colonoscope and are presented in RGB format, JPG type with the resolution of 368 * 256 pixels and 96 dpi. The name of each file (image or video) includes pathological diagnosis, grade and JNet classification of the related polyp.

BMC Research NotesVol. 17(1)
Islamic Azad University, Science and Research Branch (IR), Iran University of Medical Sciences (IR), Jahrom University of Medical Sciences (IR), Alborz University of Medical Sciences (IR), Shahid Beheshti University of Medical Sciences (IR)
Openalex Percentile: Top 21%
Colorectal Cancer Screening and Detection
0.85
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