Mojgan Forootan, Mohsen Rajabnia, Ahmad R Mafi, Hamed Azhdari Tehrani, Erfan Ghadirzadeh, Mahziar Setayeshfar, Zahra Ghaffari, Mohammad Tashakoripour, Mohammad Reza Zali, Hamidreza Bolhasani
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引用次数: 0
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 NotesBiochemistry, Genetics and Molecular Biology-Biochemistry, Genetics and Molecular Biology (all)
CiteScore
3.60
自引率
0.00%
发文量
363
审稿时长
15 weeks
期刊介绍:
BMC Research Notes publishes scientifically valid research outputs that cannot be considered as full research or methodology articles. We support the research community across all scientific and clinical disciplines by providing an open access forum for sharing data and useful information; this includes, but is not limited to, updates to previous work, additions to established methods, short publications, null results, research proposals and data management plans.