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 :
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