MR image enhancement using an extended neighborhood filter |
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| Affiliation: | 1. Medical Image Computing and Signal Processing Laboratory, Indian Institute of Information Technology and Management-Kerala, Trivandrum 695581, India;2. Department of Imaging Sciences and Interventional Radiology, SCTIMST, Trivandrum, India;1. L.I.M. Faculty of Sciences Dhar el Mahraz, USMBA, FÃs¨, Morocco;2. DESTEC, FLSHR, University of Mohammed V-Agdal, Rabat, Morocco;3. Institut Polytechnique Bordeaux/ENSEIRB-MATMECA, Laboratoire IMS CNRS UMR 5218, Groupe Signal et Image, France;4. LRIT URAC 29, University of Mohammed V-Agdal, Rabat, Morocco;1. Sichuan Province Key Lab of Signal and Information Processing, Southwest Jiaotong University, Chengdu 610031, PR China;2. School of Computer & Information Engineering, Yibin University, Yibin 644000, PR China;1. Key Lab of Intelligent Computing and Signal Processing of Ministry of Education, School of Computer Science and Technology, Anhui University, Hefei, Anhui, China;2. Department of Computer Science and Engineering, University of Texas at Arlington, Engineering Research Building, Room 529, 500 UTA Blvd, Arlington, TX 76019, USA;1. Computer and Information Technology Department, Zhejiang Police College, China;2. College of Computer Science, Zhejiang University, China |
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| Abstract: | A filtering scheme is proposed for contrast enhancement within a Region-Of-Interest (ROI) containing unconnected foreground regions of narrow spatial extent such as multiple sclerosis, or ischemic lesions in Magnetic Resonance (MR) images. This involves determination of localized multiplicative weights in the spatial domain using an extended set of neighborhood directions. The degree of enhancement is shown to depend on the number of such directions, as determined from the size of a rectangular lattice, together with a threshold value used for computing the multiplicative weights. Best performance in respect of visual quality is achieved by choosing a threshold corresponding to the maximum Contrast Ratio, and lattice size corresponding to the maximum Peak Signal-to-Noise Ratio within the ROI. It is shown that the proposed filter overrides Localized Histogram based Equalization (LHE) based techniques in terms of computational complexity, preservation of structural similarity and attaining the maximum extent of contrast stretching. |
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| Keywords: | Contrast enhancement Contrast Ratio Extended neighbors Lattice size Local Histogram Equalization Shift exponents Degree of enhancement Binary maps |
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