Image dataset for supervised learning based colonoscopy navigation systems
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资源简介：
The dataset aims to train a motorized colonoscopy system using supervised learning approaches. It includes twelve experimental scenarios (sequences). The experiments, specifically colonoscopies, were performed using a phantom colon, which is widely utilized in gastroenterology. Each image in the sequences was obtained during the colonoscope’s traveled from the rectum to the cecum. The labeled dataset consists of target steering points (along the x- and y-axes) and collision data (represented as a binary classification: 0 or 1). Note that all raw data is in .jpg format, while the labeling data is in .csv format.
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IEEE DataPort创建时间：
2025-01-24
