NDLI: Medical image fusion using the PCNN based on IQPSO in NSST domain

Content Provider	IET Digital Library
Author	Gai, Di Shen, Xuanjing Chen, Haipeng Xie, Zeyu Su, Pengxiang
Abstract	In this study, an improved quantum-behaved particle swarm optimisation based pulse-coupled neural network (IQPSO-PCNN) is proposed in the non-subsampled shearlet transform (NSST) domain for medical image fusion. First, NSST tool is used to decompose the source image into low-frequency and high-frequency subbands. Then, for low-frequency subbands, the fusion rules of two different functions are presented, which simultaneously addresses two key issues of energy preservation and detail extraction. For high-frequency subbands, unlike conventional PCNN-based methods, parameters are manually set based on experience, and the decomposed high-frequency subbands share a set of parameters. The IQPSO-PCNN model can obtain the optimal parameters for each high-frequency subband adaptively according to its own information. Finally, the fused low-frequency subband and high-frequency subbands are inversely transformed by NSST to acquire the final fused image. The proposed algorithm uses >90 pairs of images with four different modalities. In addition, fusion experiments are performed on different sequences of the three modes. The experimental results demonstrate that the proposed method is superior to existing state-of-art methods in subjective visual performance and objective evaluation.
Starting Page	1870
Ending Page	1880
Page Count	11
ISSN	17519659
Volume Number	14
e-ISSN	17519667
Issue Number	Issue 9, Jul (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/14/9
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2020.0040
Journal	IET Image Processing
Publisher Date	2020-03-10
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Biology And Medical Computing Biomedical Measurement And Imaging Computer Vision And Image Processing Technique Conventional PCNN-based Method Function Theory And Analysis Health Physics High-frequency Subband Image Denoising Image Fusion Improved Quantum-behaved Particle Swarm Optimisation Based Pulse-coupled Neural Network Integral Transforms Inverse Transforms IQPSO-PCNN Model Low-frequency Subband Medical And Biomedical Uses of Field Medical Image Fusion Medical Image Processing Neural Computing Technique Neural Nets Nonsubsampled Shearlet Transform NSST Domain Optical, Image And Video Signal Processing Optimisation Technique Particle Swarm Optimisation Patient Diagnostic Method And Instrumentation Radiations Radioactivity Sensor Fusion
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

NSST domain CT–MR neurological image fusion using optimised biologically inspired neural network

Multi-sensor image fusion based on NSST domain I2CM

Multi-focus image fusion based on non-subsampled shearlet transform

Image fusion scheme based on modified dual pulse coupled neural network

Non-subsampled shearlet transform based MRI and PET brain image fusion using simplified pulse coupled neural network and weight local features in YIQ colour space

NSCT-PCNN image fusion based on image gradient motivation

CT and MR image information fusion scheme using a cascaded framework in ripplet and NSST domain

NSST and vector-valued C–V model based image segmentation algorithm

Nonsubsampled Shearlet-based image denoising using multiscale products

Medical image fusion using the PCNN based on IQPSO in NSST domain

Similar Documents

NSST domain CT–MR neurological image fusion using optimised biologically inspired neural network

Multi-sensor image fusion based on NSST domain I2CM

Multi-focus image fusion based on non-subsampled shearlet transform

Image fusion scheme based on modified dual pulse coupled neural network

Non-subsampled shearlet transform based MRI and PET brain image fusion using simplified pulse coupled neural network and weight local features in YIQ colour space

NSCT-PCNN image fusion based on image gradient motivation

CT and MR image information fusion scheme using a cascaded framework in ripplet and NSST domain

NSST and vector-valued C–V model based image segmentation algorithm

Nonsubsampled Shearlet-based image denoising using multiscale products

Medical image fusion using the PCNN based on IQPSO in NSST domain