DocumentCode
3325425
Title
A parameterized logarithmic image processing method based on Laplacian of Gaussian filtering for lung nodules enhancement in chest radiographs
Author
Chen Bao ; Chen Sheng
Author_Institution
Sch. of Opt. Electr. & Comput. Eng., Univ. of Shanghai for Sci. & Technol., Shanghai, China
fYear
2013
fDate
23-24 Dec. 2013
Firstpage
649
Lastpage
652
Abstract
The enhancement of lung nodules in chest radiographs plays an important role in computer-aided diagnosis, and is more useful for doctor observing and analyzing. In this paper, we introduce a parameterized logarithmic image processing (PLIP) method based on Laplacian of Gaussian (LoG) filtering to enhance lung nodules in chest radiographs. This method combines the advantages of both algorithms which can enhance the lung nodules in chest radiographs (CXRs) with better image contrast and edge information. By means of measure of enhancement by entropy evaluation (EMEE) objectively, the experimental results show that the proposed method gains an effective enhancement of lung nodules in CXRs.
Keywords
Gaussian processes; computer aided engineering; diagnostic radiography; edge detection; entropy; filtering theory; image enhancement; lung; medical image processing; CXR; EMEE; Laplacian of Gaussian filtering; PLIP method; chest radiographs; computer-aided diagnosis; edge information; image contrast; lung nodule enhancement; measure of enhancement by entropy evaluation; parameterized logarithmic image processing method; Cancer; Diagnostic radiography; Filtering; Image edge detection; Laplace equations; Lungs; Laplacian of Gaussian (LoG); chest radiographs (CXRs); image enhancement; lung nodules; parameterized logarithmic image processing (PLIP);
fLanguage
English
Publisher
ieee
Conference_Titel
Instrumentation and Measurement, Sensor Network and Automation (IMSNA), 2013 2nd International Symposium on
Conference_Location
Toronto, ON
Type
conf
DOI
10.1109/IMSNA.2013.6743360
Filename
6743360
Link To Document