NDLI: De-noising of magnetic resonance images using independent component analysis

Content Provider	IEEE Xplore Digital Library
Author	Phatak, K. Jakhade, S. Nene, A. Kamathe, R.S. Joshi, K.R.
Copyright Year	2011
Description	Author affiliation: Department of electronics and telecommunication, P.E.S's Modern College of Engineering, Pune-5, Maharashtra, India (Phatak, K.; Jakhade, S.; Nene, A.; Kamathe, R.S.; Joshi, K.R.)
Abstract	Digital MR Image processing often requires a prior application of filters to reduce the noise level of the image while preserving important details. This may improve the quality of digital MR images and contribute to an accurate diagnosis. De-noising methods based on linear filters cannot preserve image structures such as edges in the same way that methods based on nonlinear filters can do it. Recently, a nonlinear de-noising method based on ICA has been introduced [1,2] for natural and artificial images. The functioning of the ICA de-noising method depends on the statistics of the images. In this paper, we show that MRI has statistics appropriate for ICA de-noising. ICA transform is applied on MRI and its 12 independent tissue components are separated and then by observing statistical properties of each component suitable sparse coding shrinkage function is applied for de-noising of each component. We demonstrate experimentally that ICA de-noising is a suitable method to remove the noise of digitized MRI.
Starting Page	807
Ending Page	812
File Size	1090862
Page Count	6
File Format	PDF
ISBN	9781424494781
e-ISBN	9781424494774
DOI	10.1109/RAICS.2011.6069421
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-09-22
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Prioritized ICA (PICA) Noise reduction Independent component analysis MRI-magnetic resonance image Vectors Covariance matrix FastICA Band-expansion process (BEP) Magnetic resonance imaging Random variables Over-complete ICA (OC-ICA) Independent component analysis (ICA) Magnetic resonance (MR) analysis Prioritized ICA band-expansion process (PICA-BEP) Principal component analysis
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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