A novel framework of multimodal medical image fusion using adaptive NSST and optimized deep learning approach

ABSTRACTMultimodal medical image fusion plays a pivotal role in the medical and imaging industry. Existing works of deep learning method suffers from blurred texture characteristics and computing efficiency. Thus, a novel deep learning model is proposed for multimodal medical image fusion. Initially, an Adaptive Non-Subsampled Shearlet Transform (ANSST) approach is developed for decomposing the images, where the filter coefficient is optimized by Hybrid Water Strider-Dingo Optimization (HWS-DOX). The fusion of the high sub-bands of source image 1 and high sub-bands of source image 2 is done by an Optimized Deep Neural Network (ODNN). Then, the lower sub-bands of source image 1 and lower sub-bands of source image 2 will be fused through a weighted averaging scheme. Finally, the final fused images are attained by applying the inverse ANSST. Thus, the performance of recommended module is compared over classical heuristics and various transform methods.KEYWORDS: Medical image fusionadaptive non-subsampled shearlet transformwater strider optimizationdingo optimizationhybrid water strider-dingo optimizationoptimized deep neural network Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationNotes on contributorsK. VanithaK. Vanitha is a research scholar in the department of ECE, JNTUA, Ananthapur, A.P, India. She received her B.Tech degree in 2010, M.Tech degree in 2013. Her areas of interest includes Biomedical image processing, optimization techniques and Soft computing techniques. She has published several papers in national and international journals. She is a life-time member in ISTE.D. SatyanarayanaDr. D. Satyanarayana received his B.Tech degree from Bharathiar University, Coimbatore, Tamil Nadu in 1992, M.Tech from J.N.T University, Hyderabad, in 1999, and Ph.D. from J.N.T University, Hyderabad in 2009. Currently, he is Controller of Examinations & Professor in the Dept. of ECE at RGMCET, Nandyal. His research areas are Speech, Signal and Image processing.M. N. GiriPrasadDr. M. N. Giri Prasad received his B.Tech degree from JNTU College of Engineering, Anantapur, A.P, India in 1982, M.Tech from Sri Venkateswara University, Tirupati, in 1994, and Ph.D. from J.N.T University, Hyderabad in 2003. Currently, he is the Director of Admissions & Professor in the Dept. of ECE at JNTUA, Anantapur. His research areas are Signal and Image processing.