Real-time automatic analysis of colonoscopies are important for learning and in practice. In
our experiment of object detection we used a Mobilenet Deep Learning model retrained on …

Deep Learning in automatic video colonoscopy processing may result in missing small
polyps or detecting them with low confidence. We conducted a study to demonstrate that we …

The growth of malignant colon polyps is a serious threat to both men's and women's lives,
and image analysis performed during a colonoscopy is the procedure that is utilized the …

Early colonoscopy diagnosis can significantly reduce the mortality rate of colon cancer
patients. Deep learning based object detection assists to enhance clinical performance on …

Although several methods for detecting and segmenting polyps during colonoscopy
procedures have been established, their generalization abilities have yet to be assessed …

Automatic polyp detection is reported to have a high false-positive rate (FPR) because of
various polyp-like structures and artifacts in complex colon environment. An efficient polyp's …

Colorectal cancer is one of the most common malignant tumors in the world. Endoscopy is
the best screening method for colorectal cancer, which uses a micro camera to enter the …

Abstract Colo-Rectal Cancer (CRC) stood witnessed as the major cause of deaths
worldwide, especially in men. But the early detection and removal of polyps can reduce the …

A major rise in the prevalence and influence of colorectal cancer (CRC) leads to
substantially increasing healthcare costs and even death. It is widely accepted that early …

Mobile networks and binary neural networks are the most commonly used techniques for
modern deep learning models to perform a variety of tasks on embedded systems. In this …