NDLI: Investigation on mammographic image compression and analysis using multiwavelets and neural network

Content Provider	IEEE Xplore Digital Library
Author	Ragupathy, U.S. Kumar, A.S.
Copyright Year	2012
Description	Author affiliation: Dept. of EIE, Dr.Mahalingam College of Engg. and Technology, Pollachi, Coimbatore District, Tamil Nadu, India (Kumar, A.S.) \|\| Dept. of EIE, Kongu Engineering College, Perundurai, Erode District, Tamil Nadu, India (Ragupathy, U.S.)
Abstract	In digital mammography, the resulting electronic image is very large in size. Hence, the size poses a big challenge to the transmission, storage and manipulation of images. Microcalcification is one of the earliest sign of breast cancer and it appears in small size, low contrast radiopacites in high frequency spectrum of mammographic image. Scalar wavelets excel multiwavelets in terms of Peak Signal - to Noise Ratio (PSNR), but fail to capture high frequency information. Multiwavelet preserves high frequency information. This paper proposes multiwavelet based mammographic image compression, and microcalcification analysis in compressed reconstructed images against original images using multiwavelets and neural networks. For a set of four mammography images, the proposed balanced multiwavelet based compression method achieves an average PSNR of 9.064 dB greater than the existing compression scheme. It also details the classification results obtained through the multiwavelet based scheme in comparison with the existing scalar wavelet based scheme. For a testing sample of 30 images, the proposed classification scheme outperforms the scalar wavelet based classification by sensitivity of 2.23% and specificity of 3.4% for original (uncompressed) images. Also it increases the sensitivity by 2.72% and specificity by 8.4% for compressed reconstructed images. This increase in sensitivity and specificity reveals a better performance of the proposed detection scheme.
Starting Page	17
Ending Page	21
File Size	1174854
Page Count	5
File Format	PDF
ISBN	9781457719905
e-ISBN	9781457719912
DOI	10.1109/ICoBE.2012.6178947
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-02-27
Publisher Place	Malaysia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Wavelet transforms Image coding PSNR Neural Network Microcalcification Hospitals Image Compression Neurons Feature extraction Mammography Image reconstruction Multiwavelet
Content Type	Text
Resource Type	Article

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