Multi-modal medical image fusion by Laplacian pyramid and adaptive sparse representation

Z Wang, Z Cui, Y Zhu - Computers in Biology and Medicine, 2020 - Elsevier
Multi-modal medical image fusion refers to the fusion of two or more medical images
obtained by different imaging methods into one image. Multi-modal medical images contain …

Medical image fusion method by using Laplacian pyramid and convolutional sparse representation

F Liu, L Chen, L Lu, A Ahmad, G Jeon… - Concurrency and …, 2020 - Wiley Online Library
Medical image fusion is a technology of combining multi‐modal images to generate a
composite image, which is favorable to improve the capability of doctors in diagnosis and …

Multi-modal medical image fusion based on two-scale image decomposition and sparse representation

S Maqsood, U Javed - Biomedical Signal Processing and Control, 2020 - Elsevier
Multimodality image fusion is the hot topic in medical imaging field which increases the
clinical diagnosis accuracy through fusing complementary information of multimodality …

Medical image fusion based on sparse representation of classified image patches

J Zong, T Qiu - Biomedical Signal Processing and Control, 2017 - Elsevier
Medical image fusion is one of the hot research in the field of medical imaging and radiation
medicine, and is widely recognized by medical and engineering fields. In this paper, a new …

Multimodal medical image fusion via laplacian pyramid and convolutional neural network reconstruction with local gradient energy strategy

J Fu, W Li, J Du, B Xiao - Computers in Biology and Medicine, 2020 - Elsevier
Background In recent years, numerous fusion algorithms have been proposed for
multimodal medical images. The Laplacian pyramid is one type of multiscale fusion method …

Medical image fusion using segment graph filter and sparse representation

Q Li, W Wang, G Chen, D Zhao - Computers in Biology and Medicine, 2021 - Elsevier
This study proposes a novel medical image fusion approach based on the segment graph
filter (SGF) and sparse representation (SR). Specifically, using the SGF, source images are …

Tensor sparse representation for 3-D medical image fusion using weighted average rule

H Yin - IEEE Transactions on Biomedical Engineering, 2018 - ieeexplore.ieee.org
Objective: The technique of fusing multimodal medical images into single image has a great
impact on the clinical diagnosis. The previous works mostly concern the two-dimensional (2 …

Multi-modality medical image fusion based on separable dictionary learning and Gabor filtering

Q Hu, S Hu, F Zhang - Signal Processing: Image Communication, 2020 - Elsevier
Sparse representation (SR) has been widely used in image fusion in recent years. However,
source image, segmented into vectors, reduces correlation and structural information of …

A novel dictionary learning approach for multi-modality medical image fusion

Z Zhu, Y Chai, H Yin, Y Li, Z Liu - Neurocomputing, 2016 - Elsevier
Multi-modality medical image fusion technology can integrate the complementary
information of different modality medical images, obtain more precise, reliable and better …

A novel approach based on three-scale image decomposition and marine predators algorithm for multi-modal medical image fusion

PH Dinh - Biomedical Signal Processing and Control, 2021 - Elsevier
Multi-modal medical image fusion not only creates an image that preserves important
information from the input images but also significantly improves in quality. This work …