TimKong21/Polyp-Segmentation
Polyp segmentation tool utilizing U-Net for accurate medical image analysis, designed to enhance early detection and diagnosis of colorectal cancer. Features a user-friendly Streamlit web app for easy image processing and analysis, leveraging the Kvasir-SEG dataset for improved healthcare outcomes.
This tool helps gastroenterologists and medical professionals improve the detection of polyps during colonoscopies. You upload colonoscopy images, and the tool uses AI to highlight potential polyps with visual segmentation masks. This aids in early diagnosis and treatment planning for colorectal cancer by reducing the chance of polyps being missed.
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Use this if you are a healthcare professional needing an automated way to assist in identifying polyps from colonoscopy images to enhance diagnostic accuracy.
Not ideal if you require a certified diagnostic tool for direct patient care, as this is an assistive tool for preliminary analysis.
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Last pushed
Feb 18, 2024
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