Integrated Multi-Source Dataset for Colorectal Polyp Detection with YOLOv11 Annotations and LOF Preprocessing

This repository contains processed versions of five publicly available colorectal polyp datasets: CVC-ColonDB, CVC-ClinicDB, Kvasir-SEG, ETIS, and CVC-300. The original datasets were publicly accessible. In this repository, segmentation masks were converted into bounding box annotations suitable for training YOLOv11-based object detection models.The data were further cleaned using a Local Outlier Factor (LOF) preprocessing method to remove anomalous samples. This processed dataset is intended to support reproducible experiments in colorectal polyp detection. The dataset includes images, masks, and labels folders for each original dataset.本仓库包含5个公开结直肠息肉数据集的处理后版本：CVC-ColonDB、CVC-ClinicDB、Kvasir-SEG、ETIS及CVC-300。原始数据集均为公开可获取的。本仓库将各原始数据集的分割掩码转换为适配基于YOLOv11的目标检测模型训练的边界框标注。此外，我们采用局部离群因子（Local Outlier Factor, LOF）预处理方法对这批数据进行清洗，以移除异常样本。本处理后的数据集旨在为结直肠息肉检测领域的可复现实验提供支撑。该数据集为每个原始数据集均提供了图像、掩码及标注文件夹。