Depth Reconstruction and Computer-Aided Polyp Detection in Optical Colonoscopy Video Frames

09/05/2016
by   Saad Nadeem, et al.
0

We present a computer-aided detection algorithm for polyps in optical colonoscopy images. Polyps are the precursors to colon cancer. In the US alone, more than 14 million optical colonoscopies are performed every year, mostly to screen for polyps. Optical colonoscopy has been shown to have an approximately 25 In this work, we present an automatic detection algorithm to detect these polyps in the optical colonoscopy images. We use a machine learning algorithm to infer a depth map for a given optical colonoscopy image and then use a detailed pre-built polyp profile to detect and delineate the boundaries of polyps in this given image. We have achieved the best recall of 84.0 best specificity value of 83.4

READ FULL TEXT

page 2

page 3

page 4

page 5

page 7

page 8

page 9

page 10

research
03/25/2022

DeepALM: Holistic Optical Network Monitoring based on Machine Learning

We demonstrate a machine learning-based optical network monitoring syste...
research
09/28/2012

A Complete System for Candidate Polyps Detection in Virtual Colonoscopy

Computer tomographic colonography, combined with computer-aided detectio...
research
02/09/2019

Lumen boundary detection using neutrosophic c-means in IVOCT images

In this paper, a novel method for lumen boundary identification is propo...
research
04/25/2018

RIFT: Multi-modal Image Matching Based on Radiation-invariant Feature Transform

Traditional feature matching methods such as scale-invariant feature tra...
research
07/27/2022

Image sensing with multilayer, nonlinear optical neural networks

Optical imaging is commonly used for both scientific and technological a...
research
07/15/2011

Astroinformatics of galaxies and quasars: a new general method for photometric redshifts estimation

With the availability of the huge amounts of data produced by current an...

Please sign up or login with your details

Forgot password? Click here to reset