Abstract
Analysis of magnetic resonance images of brain is done statistically using t test in excel and SPSS. The methodology would help the medical specialists to mechanize the examination of MRI’s of brain to differentiate the tumor from non tumor pictures to upgrade the therapeutic medical considerations. Tumor brain images can be classified from non tumor brain MRI images using a novel approach which detect grey matter in MRI images. The basic images preprocessing steps are followed like displaying of grey matter, segmentation, grey matter extraction and all is executed in Matlab environment. Statistical technique like t test in excel and SPSS is performed for classification of brain MRI images on the basis of grey matter extracted is done using Matlab. Our novel approach uses the benefits of existing preprocessing methods and filters available in Matlab for effectual extraction and analysis of brain MRI images. The work has been tested on 50 variables on forty-six subjects. Out of forty-six, twenty-four belong to healthy group and rest twenty-two belong to unhealthy. The work is assessed using t test in SPSS. The brain images are taken from the BRAINIX database and neuroimaging data repository. The proposed algorithm will be an easy approach for doctors and physicians to provide easy option for medical image analysis.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Agarwal S, Madhurima M (2016) Emotion recognition: a step ahead of traditional approaches. In: Advances in intelligent systems and computing information systems design and intelligent applications, pp 721–729
Bansal A, Yadav D (2015) Survey and comparative study on statistical tools for medical images. Adv Sci Lett Adv Sci Lett 21(1):74–77
Bhatia M, Yadav D, Gupta P, Kaur G, Singh J, Gandhi M, Singh A (2013) Implementing edge detection for medical diagnosis of a bone in Matlab. In: 5th international conference on computational intelligence and communication networks. IEEE, pp 270–274
Bhatia M, Bansal A, Yadav D, Gupta P (2015a) A proposed stratification approach for MRI images. Indian J Sci Technol 8(22). doi:10.17485/ijst/2015/v8i22/72152
Bhatia M, Bansal A, Yadav D, Gupta P (2015b) Proposed algorithm to blotch grey matter from tumored and non tumored brain MRI images. Indian J Sci Technol 8(17). doi:10.17485/ijst/2015/v8i17/63144
Cronk BC (1999) How to use SPSS: a step-by-step guide to analysis and interpretation. Pyrczak Publishing, Los Angeles
Denton ER, Holden M, Christ E, Jarosz JM, Russell-Jones D, Goodey J, Hill DL (2000) The identification of cerebral volume changes in treated growth hormone-deficient adults using serial 3D MR image processing. J Comput Assist Tomogr 24(1):139–145
DICOM Sample Image Sets (2007). Retrieved 14 Oct 2015, from http://www.osirix-viewer.com/datasets/
Display Different Image Types (2015) To display an indexed image, using either imshow or imtool, specify both the image matrix and the colormap. http://in.mathworks.com/help/images/displaying-different-image-types.html#f10-30718.2015. Accessed 12 Dec 2015
Erdi YE, Rosenzweig K, Erdi AK, Macapinlac HA, Hu Y, Braban LE, Yorke ED (2002) Radiotherapy treatment planning for patients with non-small cell lung cancer using positron emission tomography (PET). Radiother Oncol 62(1):51–60
Fei B, Wheaton A, Lee Z, Duerk JL, Wilson DL (2002) Automatic MR volume registration and its evaluation for the pelvis and prostate. Phys Med Biol 47(5):823–838
Haralick RM, Shapiro LG (1992) Computer and robot vision, 1st edn. Addison-Wesley Publishing Company, Massachusetts, MA, pp 20–23
Holden M, Hill D, Denton E, Jarosz J, Cox T, Rohlfing T, Hawkes D (2000) Voxel similarity measures for 3-D serial MR brain image registration. IEEE Trans Med Imaging 19(2):94–102
Image Processing Toolbox (2013). http://in.mathworks.com/help/images/ref/fspecial.html?s_tid=srchtitle. Accessed 2 Dec 2015
Image Processing Toolbox (2015). Retrieved 20 Dec 2015, from. http://www-rohan.sdsu.edu/doc/matlab/toolbox/images/images.html
Imfilter (2006) Retrieved 10 Jan 2016, from. http://in.mathworks.com/help/images/ref/imfilter.htm
Kagadis GC, Delibasis KK, Matsopoulos GK, Mouravliansky NA, Asvestas PA, Nikiforidis GC (2002) A comparative study of surface- and volume-based techniques for the automatic registration between CT and SPECT brain images. Med Phys 29(2):201
Kaus MR, Warfield SK, Nabavi A, Black PM, Jolesz FA, Kikinis R (2001) Automated segmentation of MR images of brain tumors 1. Radiology 218(2):586–591
Linear Filter (2013). http://www.cs.toronto.edu/~jepson/csc420/notes/linearFiltering.pdf. Accessed 15 Jan 2016
Linear Correlation Filter [Internet] (2015). https://www.cs.colostate.edu/~cs510/yr2013/Progress/L12_Filters.pdf.2014. Accessed 3 Mar 2016
Loh K, Kana D (2014) Brain scans reveal ‘grey matter’ differences in media multitaskers. Retrieved 24 Feb 2016, from. http://www.sussex.ac.uk/newsandevents/?id=26540
Miyaoka T, Seno H, Itoga M, Inagaki T, Horiguchi J (2001) Structural brain changes in schizophrenia associated with idiopathic unconjugated hyperbilirubinemia (Gilbert’s syndrome): a planimetric CT study. Schizophr Res 52(3):291–293
Moore DS (2007) The basic practice of statistics, vol 2. W.H. Freeman, New York
NITRC Neuroimaging data repository (2014). http://www.nitrc.org. Accessed 20 Jan 2016
Pandey M (2016) An amalgamated strategy for iris recognition employing neural network and hamming distance. In: Advances in intelligent systems and computing information systems design and intelligent applications, pp 739–747
Radau PE, Slomka PJ, Julin P, Svensson L, Wahlund L (2001) Evaluation of linear registration algorithms for brain SPECT and the errors due to hypoperfusion lesions. Med Phys 28(8):1660
Vaidehi K, Subashini TS (2015) Breast tissue characterization using combined K-NN classifier. Indian J Sci Technol 8(1):23
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Bhatia, M., Bansal, A. & Yadav, D. A proposed quantitative approach to classify brain MRI. Int J Syst Assur Eng Manag 8 (Suppl 2), 577–584 (2017). https://doi.org/10.1007/s13198-016-0465-8
Received:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s13198-016-0465-8