A review on multimodal medical image fusion: Compendious analysis of medical modalities, multimodal databases, fusion techniques and quality metrics
Background and objectives Over the past two decades, medical imaging has been
extensively apply to diagnose diseases. Medical experts continue to have difficulties for …
extensively apply to diagnose diseases. Medical experts continue to have difficulties for …
Current advances and future perspectives of image fusion: A comprehensive review
Multiple imaging modalities can be combined to provide more information about the real
world than a single modality alone. Infrared images discriminate targets with respect to their …
world than a single modality alone. Infrared images discriminate targets with respect to their …
Diagnosis of brain diseases in fusion of neuroimaging modalities using deep learning: A review
Brain diseases, including tumors and mental and neurological disorders, seriously threaten
the health and well-being of millions of people worldwide. Structural and functional …
the health and well-being of millions of people worldwide. Structural and functional …
Medical image fusion based on enhanced three-layer image decomposition and chameleon swarm algorithm
PH Dinh - Biomedical Signal Processing and Control, 2023 - Elsevier
Medical image fusion has brought practical applications in clinical diagnosis. However,
image fusion methods still face challenges because of problems with the quality of the input …
image fusion methods still face challenges because of problems with the quality of the input …
Multi-modal co-learning for liver lesion segmentation on PET-CT images
Liver lesion segmentation is an essential process to assist doctors in hepatocellular
carcinoma diagnosis and treatment planning. Multi-modal positron emission tomography …
carcinoma diagnosis and treatment planning. Multi-modal positron emission tomography …
Combining gabor energy with equilibrium optimizer algorithm for multi-modality medical image fusion
PH Dinh - Biomedical Signal Processing and Control, 2021 - Elsevier
Medical image fusion is a technique of extracting information from multiple image modalities
and combining them to create a single image with the aim of improving the image content …
and combining them to create a single image with the aim of improving the image content …
CT and MRI medical image fusion using noise-removal and contrast enhancement scheme with convolutional neural network
Medical image fusion (MIF) has received painstaking attention due to its diverse medical
applications in response to accurately diagnosing clinical images. Numerous MIF methods …
applications in response to accurately diagnosing clinical images. Numerous MIF methods …
From conventional approach to machine learning and deep learning approach: an experimental and comprehensive review of image fusion techniques
G Choudhary, D Sethi - Archives of Computational Methods in …, 2023 - Springer
Images captured from a single or multiple imaging sensors with considerable focus or
numerous exposures of the same or different modalities do not provide all relevant …
numerous exposures of the same or different modalities do not provide all relevant …
HID: the hybrid image decomposition model for MRI and CT fusion
Multimodal medical image fusion can combine salient information from different source
images of the same part and reduce the redundancy of information. In this paper, an efficient …
images of the same part and reduce the redundancy of information. In this paper, an efficient …
A brief analysis of multimodal medical image fusion techniques
MA Saleh, AEA Ali, K Ahmed, AM Sarhan - Electronics, 2022 - mdpi.com
Recently, image fusion has become one of the most promising fields in image processing
since it plays an essential role in different applications, such as medical diagnosis and …
since it plays an essential role in different applications, such as medical diagnosis and …