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

IF 1.6 Q2 MULTIDISCIPLINARY SCIENCES BMC Research Notes Pub Date : 2024-12-28 DOI:10.1186/s13104-024-07062-6
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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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.

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ERCPMP:结肠直肠息肉形态和病理的内镜图像和视频数据集。
该数据集包含191例结直肠息肉患者的人口统计学、形态学和病理学数据、内镜图像和视频。形态学数据包括基于最新的国际胃肠病学分类参考如巴黎,Pit和JNET分类。病理资料包括息肉的诊断,包括管状、绒毛状、管状绒毛状、增生性、锯齿状、炎性和腺癌伴不典型增生的分级和分化。目标:今天,为医学预测、检测、诊断、治疗和预后开发准确算法的最重要挑战是数据。ERCPMP是用于识别结肠直肠息肉形态和病理的内镜图像和视频数据集。该数据集可用于开发息肉检测、分类和分割的深度学习算法。数据说明:图像由奥林巴斯结肠镜拍摄,图像格式为RGB格式,JPG格式,分辨率为368 * 256像素,96 dpi。每个文件(图像或视频)的名称包括病理诊断,级别和相关息肉的JNet分类。
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来源期刊
BMC Research Notes
BMC Research Notes Biochemistry, 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.
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