Interpreting Low Resolution MRI Images Using Polynomial Based Interpolation
|International Journal of Engineering Trends and Technology (IJETT)||
|© 2014 by IJETT Journal|
|Year of Publication : 2014|
|Authors : Tarun Gulati , H.P.Sinha
Tarun Gulati , H.P.Sinha. "Interpreting Low Resolution MRI Images Using Polynomial Based Interpolation", International Journal of Engineering Trends and Technology (IJETT), V10(13),626-631 April 2014. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group
In medical imaging, image interpolation is a key aspect. Some interpolation approaches are proposed to overcome the problem of low resolution in medical imaging. MRI is an invaluable modality in the medical field. Particularly, neuro imaging with MRI helps physicians to study the internal structure and functionality of the human brain. In these cases, high resolution and isotropic images are important because higher isotropic resolution could theoretically reduce partial volume artifacts, leading to better accuracy/precision in deriving volumetric measurement and decreasing considerable errors in registration . In this case, invaluable information will be lost in the latter direction. The objective is to recover and fill in this missing information in order to enable the physicians to obtain a more accurate perspective of the underlying structure available in the data by optimizing the choice of interpolation techniques. Therefore, this paper focuses on investigating the effect of various polynomial based interpolation functions on zooming low resolution images.
 Dimitri Van De Ville, Rik Van de Walle, Wilfried Philip2, Ignace Lemahieu, “ Image Resampling Between Orthogonal And Hexagonal Lattices,” IEEE ICIP 2002, pp 389-392
 King-Hong Chung, Yik-Hing Fung and Yuk-Hee Chan, “Image Enlargement using Fractal,” ICASSP 2003, pp 273-276.
 Mohiy M. Hadhoud, Moawad I. Dessouky, Fathi E. Abd El-Samie, “Adaptive Image Interpolation Based On local Activity levels,” Twenteith National Radio Science Conference, March 18-20,2003, Cairo, Egypt.
 Henrique S. Malvar, Li-wei He, and Ross Cutler, “High-Quality Linear Interpolation For Demosaicing Of Bayer-Patterned Color Images,” ICASSP 2004, pp 485-488
 Zhen Ye, Jasjit Suri, Yajie Sun, Roman Janer, “Four Image Interpolation Techniques for Ultrasound Breast Phantom Data Acquired Using Fischer`s Full Field Digital Mammography and Ultrasound System (FFDMUS): A Comparative Approach,” IEEE, 2005
 Day-Fann Shen , Chui-Wen Chiu, Pon-Jay Huang, “Modified Laplacian Filter And Intensity Correction Technique For Image Resolution Enhancement,” ICME 2006, pp 457-460
 Xiangjian He, Wenjing Jia, Jianmin Li, Qiang Wu, Tom Hintz, “An Approach to Edge Detection on a Virtual Hexagonal Structure,” Digital Image Computing Techniques and Applications, IEEE computer Society, 2007, pp 340-345.
 Hamid Gharavi, and Shaoshuai Gao, “Spatial Interpolation Algorithm For Error Concealment,” ICASSP 2008, pp 1153-1156.
 Prasantha H S, Shashidhara H L, Balasubramanya Murthy K N, “Image Scaling Comparison Using Universal Image Quality Index,” International Conference on Advances in Computing, Control, and Telecommunication Technologies, 2009, pp 859-863.
 Deep Bera, Leeladhar Agarwal and Swapna Banerjee, “Multirate Scan Conversion of Ultrasound images using warped distance based adaptive bilinear interpolation,” IEEE, 2009.
 Li Zhiwei, Zhang Min, Wang Jiechao, “An Image Zooming Technique Based on the Relative Color Difference of Pixels,” 2nd International Conference on Signal Processing Systems (ICSPS), 2010, pp 46-49.
 G.Uma Vetri Selvi, R.Nadarajan, “DICOM Image compression using Bilinear Interpolation,” IEEE,2010.
 Jie Li, Mingrui Xin, Jianong Jin, “An Evolutionary approach for Gray-level Image Zooming,” AHS-2011, pp 383-389.
 Ganga Mohan P, Chetana Prakash, Surayakanth V. Gangashetty, “Bessel Transform for Image Resizing,” 2011
 PeiyiSheu, LiangZhang, ZhijianWangl, , WeiShan, Zhengchuanuu, XiangdongZhang, Yizhe Song, “ A Novel Interpolation Algorithm For Non-Linear Omni-Catadioptric Images,” ProceedingsofIC-NIDC2012, pp 508-511.
Pixel, Quantization, Sampling, zooming and interpolation.