Recognition of brain stroke shape using multiscale morphological image processing

ABSTRACT

Brain haemorrhage is a form of stroke caused by the inflation in the cerebral artery ensuing confined bleeding in the inherent tissues. The MRI images (T1, T2 and FLAIR (fluid-attenuated inversion recovery)) are extracted from Siemen 3T scanner in which the ordinary and haemorrhage-affected strokes are effectively emphasized in this work. The existing such as CNN (convolutional neural network), residual CNN and MCDNN (mobile-cloud deep neural network) are compared from the perspective of PSNR (peak signal-to-noise ratio), SSIM (structural similarity index measure) and MSE (mean squared error), respectively. The PSNR value of this proposed MMNN (multiple nonotonic neural network) is increased by 0.23%, 0.087% and 0.613% compared to CNN, Residual CNN and MCDNN techniques, respectively. The SSIM value is increased by 0.57%, 0.322% and 0.027% compared to CNN, Residual CNN and MCDNN. MSE value is decreased by 8.93%, 2.1457% and 0.316% compared to CNN, Residual CNN and MCDNN, respectively.

KEYWORDS:

• Brain haemorrhage
• T1
• T2 & FLAIR (fluid-attenuated inversion recovery) images
• deep learning
• multiscale morphological neural network
• SIEMEN 3T scanner

Acknowledgement

The authors would like to thank Anna University and also we like to thank Anonymous reviewers for their so-called insights.

Disclosure statement

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

Additional information

Notes on contributors

S. Venkata Lakshmi

Dr S. Venkata Lakshmi currently serves as a Professor and Head of the Department of Artificial Intelligence and Data Science, Sri Krishna College of Engineering and Technology, Coimbatore. She received her Doctorate Degree of Computer Science and Engineering from Manonmaniam Sundaranar University. She has an experience of around 20 years in teaching and published journals in peer reviewed journals, Patents and book chapters in her area of interest and also presented papers in various International/National conferences. Her research interest includes Image Processing, Artificial Intelligence, Network Security and Information Retrieval.

M. Anline Rejula

Dr M. Anline Rejula, received her doctoral degree in Computer Applications in 2021, M.Phil. (Computer Science) in 2004, Master of Computer Applications (MCA) in 2002 and Graduation in BSc Mathematics in 1999 from Manonmaniam Sundaranar University, Tirunelveli. She had worked as a faculty member in SSI, Thiruvananthpuram and in a renowned school, Christhu Raja Matric Higher Secondary School, Marthandam. She had more than thirteen years of experience in Noorul Islam College of Arts and Science, Kumaracoil. Now she is working as an Assistant Professor in the Department of ComputerApplications-PG, Scott Christian College (Autonomous), Nagercoil. In addition to that she has published papers on Image Processing, Deep learning, Network security, Cloud Computing, and books on Relational Database Management System, Internet of Things and Machine Learning using Python.

K. Sujatha

Dr K. Sujatha is working as an Assistant professor in Department of Computer Science Kean Wenzhou University China and active member of CSI with 22 years of teaching experience. Her specialization is computer vision and machine learning. She has published papers in International refereed journals like Springer and Elsevier. She has delivered several guest lectures, seminars and chaired a session for various Conferences. She is serving as a Reviewer and Editorial Board Member of many reputed Journals and acted as Session chair and Technical Program Committee member of National conferences and International Conferences. She has received a best researcher award during her research period. She one of the member of Zhejiang Bioinformatics International Science and Technology Cooperation Center, Wenzhou-Kean University, Wenzhou, Zhejiang Province, China, Wenzhou Municipal Key Lab of Applied Biomedical and Biopharmaceutical Informatics, Wenzhou-Kean University, Wenzhou, Zhejiang Province, China.

A. Ahilan

Dr A. Ahilan received Ph.D. from Anna University, India, and working as an Associate Professor in the Department of Electronics and Communication Engineering at PSN College of Engineering and Technology, India. His area of interest includes FPGA prototyping, Computer vision, the Internet of Things, Cloud Computing in Medical, biometrics, and automation applications. Served Guest editor in several journals of Elsevier, Bentham, IGI publishers. Also, have contributed original research articles in IEEE Transactions, SCI, SCIE, and Scopus indexed peer-review journals. He presented various international conference events like ASQED (Malaysia), ESREF (France). He is doing as a reviewer in IEEE Industrial Informatics, IEEE Access, Measurement, Multimedia Tools & Applications, Computer Networks, Medical systems, Computer & Electrical Engineering, neural computing and applications, Cluster Computing, IET Image Processing, and so on. He has IEEE and ISTE membership. He has worked as a Research Consultant at TCS, Bangalore, where he has guided many computer vision projects and Bluetooth Low Energy projects. Hands on programming in MATLAB, Verilog and python at various technical institutions around India.