Paper Info
Title
A new preprocessing filter for digital mammograms
Abstract
This paper presents a computer-aided approach to enhancing suspicious lesions in digital mammograms. The developed algorithm improves on a well-known preprocessor filter named contrast-limited adaptive histogram equalization (CLAHE) to remove noise and intensity inhomogeneities. The proposed preprocessing filter, called fuzzy contrast-limited adaptive histogram equalization (FCLAHE), performs non-linear enhancement. The filter eliminates noise and intensity inhomogeneities in the background while retaining the natural gray level variations of mammographic images within suspicious lesions. We applied Catarious segmentation method (CSM) to compare the segmentation accuracy in two scenarios: when there is no preprocessing filter, and when the proposed preprocessing filter is applied to the original image. The proposed filter has been evaluated on 50 real mammographic images and the experimental results show an average increase of segmentation accuracy by 14.16% when the new filter is applied.
Year
DOI
Venue
2010
10.1007/978-3-642-13681-8_68
ICISP
Keywords
Field
DocType
segmentation accuracy,contrast-limited adaptive histogram equalization,digital mammograms,fuzzy contrast-limited adaptive histogram,new filter,catarious segmentation method,proposed preprocessing filter,proposed filter,preprocessing filter,suspicious lesion,intensity inhomogeneities,new preprocessing filter,breast cancer,histogram equalization,segmentation
Computer vision,Mammography,Scale-space segmentation,Pattern recognition,Computer science,Segmentation,Fuzzy logic,Adaptive histogram equalization,Preprocessor,Image denoising,Artificial intelligence,Gray level
Conference
Volume
ISSN
ISBN
6134
0302-9743
3-642-13680-X
Citations 
PageRank 
References 
2
0.38
5
Authors
4
Name
Order
Citations
PageRank
Peyman Rahmati1282.17
Ghassan Hamarneh21353110.14
Doron Nussbaum38913.49
Andy Adler4575.49