Colon Polyps Detection from Colonoscopy Images Using Deep Learning

• URL: http://arxiv.org/abs/2508.13188v1
• Date: Thu, 14 Aug 2025 20:16:23 GMT
• Title: Colon Polyps Detection from Colonoscopy Images Using Deep Learning
• Authors: Md Al Amin, Bikash Kumar Paul,
• Abstract summary: Colon polyps are precursors to colorectal cancer, a leading cause of cancer-related mortality worldwide.<n>This study investigates the application of deep learning-based object detection for early polyp identification using colonoscopy images.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Colon polyps are precursors to colorectal cancer, a leading cause of cancer-related mortality worldwide. Early detection is critical for improving patient outcomes. This study investigates the application of deep learning-based object detection for early polyp identification using colonoscopy images. We utilize the Kvasir-SEG dataset, applying extensive data augmentation and splitting the data into training (80\%), validation (20\% of training), and testing (20\%) sets. Three variants of the YOLOv5 architecture (YOLOv5s, YOLOv5m, YOLOv5l) are evaluated. Experimental results show that YOLOv5l outperforms the other variants, achieving a mean average precision (mAP) of 85.1\%, with the highest average Intersection over Union (IoU) of 0.86. These findings demonstrate that YOLOv5l provides superior detection performance for colon polyp localization, offering a promising tool for enhancing colorectal cancer screening accuracy.

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