title: Tumor or abnormality identification from magnetic resonance images using statistical region fusion based segmentation.
abstract: In this article, a statistical fusion based segmentation technique is proposed to identify different abnormality in magnetic resonance images (MRI). The proposed scheme follows seed selection, region growing-merging and fusion of multiple image segments. In this process initially, an image is divided into a number of blocks and for each block we compute the phase component of the Fourier transform. The phase component of each block reflects the gray level variation among the block but contains a large correlation among them. Hence a singular value decomposition (SVD) technique is adhered to generate a singular value of each block. Then a thresholding procedure is applied on these singular values to identify edgy and smooth regions and some seed points are selected for segmentation. By considering each seed point we perform a binary segmentation of the complete MRI and hence with all seed points we get an equal number of binary images. A parcel based statistical fusion process is used to fuse all the binary images into multiple segments. Effectiveness of the proposed scheme is tested on identifying different abnormalities: prostatic carcinoma detection, tuberculous granulomas identification and intracranial neoplasm or brain tumor detection. The proposed technique is established by comparing its results against seven state-of-the-art techniques with six performance evaluation measures.
authors.affiliation: Department of Electronics and Communication Engineering, National Institute of Technology Goa, Farmagudi, Ponda, Goa, 403401, India. Electronic address: subudhi.badri@gmail.com.
authors.forename: Badri Narayan
authors.initials: BN
authors.lastname: Subudhi
authors.affiliation: Department of Electronics and Communication Engineering, National Institute of Technology Goa, Farmagudi, Ponda, Goa, 403401, India. Electronic address: tveerakumar@yahoo.co.in.
authors.forename: Veerakumar
authors.initials: V
authors.lastname: Thangaraj
authors.affiliation: Department of Instrumentation and Control Engineering, PSG College of Technology, Coimbatore, India. Electronic address: rajanesakki@yahoo.com.
authors.forename: Esakkirajan
authors.initials: E
authors.lastname: Sankaralingam
authors.affiliation: Machine Intelligence Unit, Indian Statistical Institute, Kolkata, 700108, India. Electronic address: ash@isical.ac.in.
authors.forename: Ashish
authors.initials: A
authors.lastname: Ghosh
mesh_terms: D000465:Algorithms; D001932:Brain Neoplasms / Q000000981:diagnostic imaging*; D005583:Fourier Analysis; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods* / Q000706:statistics & numerical data*; D008279:Magnetic Resonance Imaging / Q000379:methods* / Q000706:statistics & numerical data*; D008297:Male; D011471:Prostatic Neoplasms / Q000000981:diagnostic imaging*; D014375:Tuberculoma / Q000000981:diagnostic imaging*
keywords: Image segmentation; Parcel creation; Region growing; Statistical merging