Distance Metric-based Segmentation and Score-Level Classification for Optimized Tumor Identification in MR Images

Abstract

Tumors in the brain and pancreas are formed by abnormal cells accumulating in a tissue mass in the human body. The standard technique for MRI tumor detection and categorization would be to investigate them utilizing MR medical images. Due to a discrepancy among many brain and image characteristics, an MR picture is segmented at the early stage of diagnosis. The tumor identification framework is processed in the following order: The initial pre-processing (or) filtering is carried out using a Modified Decision-Based Coupled Windows Median Filter (MDBCWMF) technique. This stage's output is transmitted to a unique Distance Metric-based variant of the Fuzzy C-Means algorithm for segmenting MDM-FCM. This method results in a lower segmentation error. The image is then feature extracted using a Gray-Level Co-Occurrence Matrix (GLCM) algorithm and classified using a parameterized combination of Back Propagation Neural Network (BPNN) and Sparse Representation (SR) approaches known as Dynamic Score Level Integration (DSLI). Compared to other state-of-the-art methodologies, MDM-FCM segmented yields 0.9674 and 0.9481 in classification yield 97.84% and 95.62% accuracy for brain and pancreas images, experimental valuation being done with Datasets from TCIA.

KEYWORDS:

• BPNN
• DSLI
• GLCM
• MDBCWM filter
• Modified Distance Metric of FCM
• SR
• TCIA

ACKNOWLEDGEMENTS

The authors thank the management of Kalasalingam Academy of Research and Education for providing fellowship and also the VLSI DST-FIST Research Centre for supporting laboratory facilities during this research work. The authors are thankful to Dr. Daggumati Shrehari Rao, Radiologist, Chairman & Administrative Committee Member of Andhra Pradesh Medical Council Vijayawada (Indian Government) for providing necessary patient information and images for supporting research.

Additional information

Notes on contributors

D. Jithendra Reddy

D Jithendra Reddy is research scholar in the Department of Instrumentation and Control Engineering at Kalasalingam Academy of Research and Education. He pursued his Master of Technology in digital systems and computer electronics from JNTU Ananthapur University in 2015 and BTech in electronics and instrumentation engineering from JNTU Ananthapur University in 2011. His areas of interest are medical image processing and biomedical instrumentation. Corresponding author. Email: [email protected]

T. Arun Prasath

T Arun Prasath is an associate professor in Department Biomedical Engineering at Kalasalingam Academy of Research and Education. He received his PhD in electronics and communication engineering from Kalasalingam University, Krishnankoil in 2015, his ME in applied electornics from Anna University in 2009 (Mohamed Sathak Engineering College) and his BE in electrical and electronics engineering from Anna University (Syed Ammal Engineering College) in 2006. His research interests include biomedical instrumentation, image processing, and cloud computing. He has published research articles in 30 technical journals and 40 technical papers in refereed conferences in these areas. He is a life member of ISTE. Email: [email protected]

M. Pallikonda Rajasekaran

M Pallikonda Rajasekaran is a professor in Department of Electronics and Communication Engineering at Kalasalingam University. He received his PhD in electrical and electronics engineering from Anna University, Chennai in 2009, his MTech in biomedical signal processing and instrumentation from SASTRA University in 2002 and his BE in electronics and instrumentation engineering from Bharathidasan University (Shanmuga College of Engineering) in 2001. His research interests include biomedical instrumentation, image processing, wireless sensor networks, high performance computing, sensor systems, cloud computing, semantic networks. He has published numerous technical papers in refereed conferences and journals in these areas. He is a senior member of the International Association of Computer Science And Information Technology (IACSIT), Asia-Pacific Chemical, Biological & Environmental Engineering Society (APCBEES), Biomedical Society of India and Indian Society for Technical Education (ISTE). Email: [email protected]