Using Pareto fronts to evaluate polyp detection algorithms for CT colonography

2007 ◽  
Author(s):  
Adam Huang ◽  
Jiang Li ◽  
Ronald M. Summers ◽  
Nicholas Petrick ◽  
Amy K. Hara
Keyword(s):  
Ct Colonography ◽  
Polyp Detection ◽  
Detection Algorithms ◽  
Pareto Fronts

scholarly journals Improving polyp detection algorithms for CT colonography: Pareto front approach

2010 ◽  
Vol 31 (11) ◽  
pp. 1461-1469 ◽  
Author(s):  
Adam Huang ◽  
Jiang Li ◽  
Ronald M. Summers ◽  
Nicholas Petrick ◽  
Amy K. Hara
Keyword(s):  
Ct Colonography ◽  
Pareto Front ◽  
Polyp Detection ◽  
Detection Algorithms

T1229 CT Colonography: Polyp Detection and Endoscopic Follow up in an Urban UK Hospital Cohort

2010 ◽  
Vol 138 (5) ◽  
pp. S-516
Author(s):  
Lolita Chan ◽  
Javaid Iqbal ◽  
Andrew Mcpartlin ◽  
Tuheen Huda ◽  
Robert P. Willert
Keyword(s):  
Ct Colonography ◽  
Polyp Detection

Primary 2D Versus Primary 3D Polyp Detection at Screening CT Colonography

2007 ◽  
Vol 189 (6) ◽  
pp. 1451-1456 ◽  
Author(s):  
Perry J. Pickhardt ◽  
Andrew D. Lee ◽  
Andrew J. Taylor ◽  
Steven J. Michel ◽  
Thomas C. Winter ◽  
...  
Keyword(s):  
Ct Colonography ◽  
Polyp Detection

scholarly journals Improved diagnosis and navigation for CT colonography

2021 ◽  
Author(s):  
Jinjie Ming
Keyword(s):  
Ct Colonography ◽  
Automatic Segmentation ◽  
Segmentation Method ◽  
Polyp Detection ◽  
Data Set ◽  
Colon Wall ◽  
Texture Information ◽  
Ct Data ◽  
New Feature ◽  
Shape And Size

This project describes the development of an automatic segmentation method and a novel navigation system that detect polyps using advanced image processing and computer graphics tecniques. The colon wall segmentation method from the CT data set of abdomen is achieved by combining the contouring model - level set method and the minima detection using mathematical morphology theory. Polyp detection is attained by analyzing surface curvature and texture information along on the colon wall. Adding texture analysis provides a new feature for improving currently existing methods. As such, polyp candidates are examined not only by their shape and size but also by their texture appearance.

scholarly journals A Pipeline for Computer Aided Polyp Detection and Segmentation in Ct Colonography

2014 ◽  
Vol 9 (4) ◽  
pp. 68-75
Author(s):  
Janapriya A.S ◽  
◽  
Mythili C ◽  
Nishanthi P ◽  
Sunitha K
Keyword(s):  
Ct Colonography ◽  
Polyp Detection ◽  
Computer Aided

scholarly journals Improved diagnosis and navigation for CT colonography

2021 ◽  
Author(s):  
Jinjie Ming
Keyword(s):  
Ct Colonography ◽  
Automatic Segmentation ◽  
Segmentation Method ◽  
Polyp Detection ◽  
Data Set ◽  
Colon Wall ◽  
Texture Information ◽  
Ct Data ◽  
New Feature ◽  
Shape And Size

This project describes the development of an automatic segmentation method and a novel navigation system that detect polyps using advanced image processing and computer graphics tecniques. The colon wall segmentation method from the CT data set of abdomen is achieved by combining the contouring model - level set method and the minima detection using mathematical morphology theory. Polyp detection is attained by analyzing surface curvature and texture information along on the colon wall. Adding texture analysis provides a new feature for improving currently existing methods. As such, polyp candidates are examined not only by their shape and size but also by their texture appearance.

Sign in / Sign up

Export Citation Format

Share Document