Title
On Normalized Convolution to Measure Curvature Features for Automatic Polyp Detection
Abstract
Early removal of polyps has proven to decrease the incidence of colon cancer. We aim to increase the sensitivity of the screening by automatic detection of polyps. It requires accurate measurement of the colon wall curvature. This paper describes a new method which computes the curvatures using space-variant derivative operators in a strip along the edge of the colon. It optimizes the trade-off between noise reduction and mixing of adjacent image structures. The derivative operators incorporate an applicability function for regularization and interpret the strips as confidence measure; certain inside and uncertain outside. To that purpose the technique of normalized convolution is utilized and adapted to allow a local Taylor expansion of the image signal. A special scheme to compute the confidence values is also presented.
Year
DOI
Venue
2004
10.1007/978-3-540-30135-6_25
Lecture Notes in Computer Science
Keywords
Field
DocType
noise reduction,colon cancer,taylor expansion
Noise reduction,Normalization (statistics),Curvature,Pattern recognition,Convolution,Computer science,Regularization (mathematics),STRIPS,Operator (computer programming),Artificial intelligence,Taylor series
Conference
Volume
ISSN
Citations 
3216
0302-9743
10
PageRank 
References 
Authors
1.14
4
5
Name
Order
Citations
PageRank
Cees van Wijk1725.13
Roel Truyen221819.37
Rogier van Gelder3202.70
Lucas J. van Vliet4842113.16
Frans Vos510611.97