CVC PolypHD - sporedata/researchdesigneR GitHub Wiki

General description

The CVC-PolypHD dataset is a large, high-definition image dataset primarily used in the context of colonoscopy research for detecting and segmenting polyps. Polyps are abnormal growths in the colon or rectum that can potentially develop into colorectal cancer if left untreated. Early detection through screening methods like colonoscopy is crucial for preventing cancer, and the CVC-PolypHD dataset contributes significantly to the development of advanced computer vision and AI models for automated polyp detection.

The CVC-PolypHD dataset plays a significant role in advancing AI-driven colorectal cancer screening tools. By improving the accuracy and speed of polyp detection, AI models trained on this dataset can help detect polyps that might otherwise be missed by the human eye, leading to earlier intervention and better patient outcomes.

In summary, the CVC-PolypHD dataset is a valuable resource for researchers working on medical imaging, particularly in the area of colorectal cancer prevention. It supports the development of robust AI models for polyp detection and segmentation, which are critical for improving colonoscopy outcomes and reducing colorectal cancer incidence

Limitations

  1. Size of polyps: Polyps can vary significantly in size, from small and flat lesions to large, protruding ones. This variance necessitates models that can generalize across different polyp types.

  2. Lighting conditions: Colonoscopy videos and images may suffer from variable lighting and occlusions, which complicates image processing and AI detection efforts

  3. Variability in polyp appearance: Polyps can appear in various shapes, colors, and textures, often blending in with the surrounding mucosal tissue, making detection challenging.

Related publications

Data access

For more information on the CVC-PolypHD dataset, visit https://giana.grand-challenge.org/