An advanced fuzzy C-Means algorithm for the tissue segmentation from brain magnetic resonance images in the presence of noise and intensity inhomogeneity

ABSTRACT

Segmentation of brain Magnetic Resonance Images (MRIs) into various brain tissues such as white matter (WM), grey matter (GM), and cerebrospinal fluid (CSF) is very important to detect and diagnose different brain-related disorders at the primitive level. Accurate segmentation of brain MRIs is very difficult because of the intricate anatomical structure of the tissues, the existence of Intensity Inhomogeneity (IIH), noise, and Partial Volume Effects (PVE). Clustering-based methods are generally used to segment brain images. This work proposes a Chaotic based Enhanced Firefly Algorithm Integrated with Fuzzy C-Means (CEFAFCM) for the segmentation of brain tissues WM, GM, and CSF from brain MRIs. The proposed method can handle IIH, PVE, and noise. CEFAFCM is a spatially modified FCM algorithm combined with the Firefly Algorithm (FA) along with a chaotic map for the initialization of the population of fireflies. The algorithm is tested with brain MRIs acquired from the BrainWeb database. The experimental results demonstrate that the proposed technique is producing better results in comparison with some existing brain MRI segmentation methods such as FCM, BCFCM, FAFCM, and En-FAFCM.

KEYWORDS:

• MRI
• brain tissues
• FCM
• BCFCM
• FAFCM
• En-FAFCM
• CEFAFCM

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Sandhya Gudise

Sandhya Gudise received her PhD from Jawaharlal Nehru Technological University, Kakinada and working as an Associate professor in Electronics and Communication Department in VNITSW, Guntur. She received the master’s degree in instrumentation and control systems from JNTU College of Engineering, Kakinada. Her research interests focus on the medical image processing, with specific emphasis on the detection of normal and abnormal tissues in MR images of the brain. She published many research papers in various SCI, Scopus indexed journals and in national and international conferences.

K. Giri Babu

K. Giri Babu is a professor in Electronics and Communication Department in VVIT, Guntur. He has teaching experience of about 20 years. He is guiding many UG, PG projects, and research scholars. His research interests include digital image processing, VLSI, and communication. He received the PhD degree in digital image processing from Jawaharlal Nehru Technological University, Hyderabad. He is a member of various professional chapters and published many research papers in various SCI journals and national and international conferences.

T. Satya Savithri

T. Satya Savithri is a professor in Electronics and Communication Department of Jawaharlal Nehru Technological University, Hyderabad. She has teaching experience of about 20 years. She received the PhD degree in image processing from Jawaharlal Nehru Technological University, Hyderabad. Her research interests include DIP, VLSI, microwaves, and communication. She is a member of ISTE, IEI, and published many research papers in various SCI journals and conferences. She is guiding many UG, PG, and funded projects and also 15 research scholars.