CP-CHILD.zip

CP-CHILD records the colonoscopy data of children. It contains two datasets CP-CHILD-A and CP-CHILD-B. The CP-CHILD-A dataset contains 8000 RGB images taken by Olympus PCF-H290DI, including 1000 colonic polyp images and 7000 normal or other pathological images. The CP-CHILD-B dataset contains 1500 RGB images taken by FUJIFLIM EC-530wm, including 400 colonic polyp images and 1100 normal or other pathological images. Using the deep learning model on this dataset, we can classify the objects in the dataset. Neural network's self-learning and self-training ability can improve the adaptability, efficiency and detection accuracy of children's colonoscopy CAD.

CP-CHILD数据集（CP-CHILD）收录儿童结肠镜检查相关数据，包含CP-CHILD-A与CP-CHILD-B两个子数据集。CP-CHILD-A子数据集包含由奥林巴斯（Olympus）PCF-H290DI肠镜设备采集的8000幅RGB图像，其中涵盖1000幅结肠息肉图像以及7000幅正常或其他病理图像。CP-CHILD-B子数据集包含由富士胶片（FUJIFLIM）EC-530wm肠镜设备采集的1500幅RGB图像，其中涵盖400幅结肠息肉图像以及1100幅正常或其他病理图像。基于该数据集训练深度学习模型，可实现对数据集中样本的分类任务。神经网络所具备的自学习与自训练能力，能够提升儿童结肠镜检查计算机辅助诊断（CAD）的适配性、检测效率与诊断准确率。

搜集汇总

背景与挑战

背景概述

CP-CHILD.zip是一个儿童结肠镜检查图像数据集，包含两个子数据集，分别由不同设备拍摄，用于深度学习模型的训练和结肠息肉分类。