A novel intuitionistic fuzzy co-clustering algorithm for brain images
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A novel intuitionistic fuzzy co-clustering algorithm for brain images Om Prakash Verma 1 & Heena Hooda 2 Received: 6 June 2019 / Revised: 10 April 2020 / Accepted: 9 July 2020 # Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract
Segmentation of Magnetic Resonance Imaging(MRI) Brain images is a very important step in detection of brain tumor. This process is hand operated in labs which is rather an enervating and a long drawn out task and the resultant data so obtained has high degree of erroneity and inconsistency. Hence, automated segmentation systems have become the need of the hour. This paper presents a novel technique to automatically detect brain tumor. Also, segmentation of three main brain tissues is carried out namely white matter, gray matter and cerebrospinal fluid from real time Magnetic Resonance Imaging(MRI) images. The Intuitionistic Fuzzy Set theory is incorporated as it is more suitable for handling uncertainty as compared to fuzzy sets theory. The algorithm is based on the CoClustering approach as it offers the advantage of assigning membership functions to both object as well as features. The parameters in the IFCC algorithm are optimized using Particle Swarm Optimization(PSO). The performance of the algorithm is evaluated on the basis of quantitative measures such as match score, accuracy score, dice score and Jaccard’s similarity coefficient. Keywords Magnetic resonance imaging . Intuitionistic fuzzy sets . Fuzzy co-clustering . Tumor detection
1 Introduction Magnetic Resonance Imaging (MRI) is one of the techniques of imaging technology which is widely used for high quality medical images [6, 16, 22]. Unlike imaging using radiation, in * Heena Hooda [email protected] Om Prakash Verma [email protected]
1
GB Pant Govt. Engineering College, Delhi, India
2
Department Of IT, Delhi Technological University, Delhi, India
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which the contrast depends on the different attenuations of the structures being imaged, the contrast in MR images depends on the magnetic properties and number of hydrogen nuclei in the area being imaged. Different contrasts in the area being imaged can be selected by running different sequences with different weightings. Echo Time(TE) is the time between the 90° Radio Frequency pulse and MR signal sampling, corresponding to maximum of echo. The 180° RF pulse is applied at time TE/2. Repetition Time(TR) is the time between 2 excitation pulse. The three main sequences are namely T1-weighted, T2-weighted and Proton Density (PD) weighted depending on the TR and TE sequence. A long TR and a short TE sequence is usually called Proton density -weighted. A short TR and a short TE sequence is usually called T1-weighted. A long TR and a long TE sequence is usually called T2-weighted. MRI is especially used in brain imaging, as it can detect variety of conditions of the brain such as cysts, tumors, bleeding, swelling and discover other such abnormalities of brain. The growth of abnormal cells in the tissues of the bra
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